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Survey Research – Types, Methods, Examples

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Survey Research

Definition:

Survey Research is a quantitative research method that involves collecting standardized data from a sample of individuals or groups through the use of structured questionnaires or interviews. The data collected is then analyzed statistically to identify patterns and relationships between variables, and to draw conclusions about the population being studied.

Survey research can be used to answer a variety of questions, including:

• What are people’s opinions about a certain topic?
• What are people’s experiences with a certain product or service?
• What are people’s beliefs about a certain issue?

Survey Research Methods

Survey Research Methods are as follows:

• Telephone surveys: A survey research method where questions are administered to respondents over the phone, often used in market research or political polling.
• Face-to-face surveys: A survey research method where questions are administered to respondents in person, often used in social or health research.
• Mail surveys: A survey research method where questionnaires are sent to respondents through mail, often used in customer satisfaction or opinion surveys.
• Online surveys: A survey research method where questions are administered to respondents through online platforms, often used in market research or customer feedback.
• Email surveys: A survey research method where questionnaires are sent to respondents through email, often used in customer satisfaction or opinion surveys.
• Mixed-mode surveys: A survey research method that combines two or more survey modes, often used to increase response rates or reach diverse populations.
• Computer-assisted surveys: A survey research method that uses computer technology to administer or collect survey data, often used in large-scale surveys or data collection.
• Interactive voice response surveys: A survey research method where respondents answer questions through a touch-tone telephone system, often used in automated customer satisfaction or opinion surveys.
• Mobile surveys: A survey research method where questions are administered to respondents through mobile devices, often used in market research or customer feedback.
• Group-administered surveys: A survey research method where questions are administered to a group of respondents simultaneously, often used in education or training evaluation.
• Web-intercept surveys: A survey research method where questions are administered to website visitors, often used in website or user experience research.
• In-app surveys: A survey research method where questions are administered to users of a mobile application, often used in mobile app or user experience research.
• Social media surveys: A survey research method where questions are administered to respondents through social media platforms, often used in social media or brand awareness research.
• SMS surveys: A survey research method where questions are administered to respondents through text messaging, often used in customer feedback or opinion surveys.
• IVR surveys: A survey research method where questions are administered to respondents through an interactive voice response system, often used in automated customer feedback or opinion surveys.
• Mixed-method surveys: A survey research method that combines both qualitative and quantitative data collection methods, often used in exploratory or mixed-method research.
• Drop-off surveys: A survey research method where respondents are provided with a survey questionnaire and asked to return it at a later time or through a designated drop-off location.
• Intercept surveys: A survey research method where respondents are approached in public places and asked to participate in a survey, often used in market research or customer feedback.
• Hybrid surveys: A survey research method that combines two or more survey modes, data sources, or research methods, often used in complex or multi-dimensional research questions.

Types of Survey Research

There are several types of survey research that can be used to collect data from a sample of individuals or groups. following are Types of Survey Research:

• Cross-sectional survey: A type of survey research that gathers data from a sample of individuals at a specific point in time, providing a snapshot of the population being studied.
• Longitudinal survey: A type of survey research that gathers data from the same sample of individuals over an extended period of time, allowing researchers to track changes or trends in the population being studied.
• Panel survey: A type of longitudinal survey research that tracks the same sample of individuals over time, typically collecting data at multiple points in time.
• Epidemiological survey: A type of survey research that studies the distribution and determinants of health and disease in a population, often used to identify risk factors and inform public health interventions.
• Observational survey: A type of survey research that collects data through direct observation of individuals or groups, often used in behavioral or social research.
• Correlational survey: A type of survey research that measures the degree of association or relationship between two or more variables, often used to identify patterns or trends in data.
• Experimental survey: A type of survey research that involves manipulating one or more variables to observe the effect on an outcome, often used to test causal hypotheses.
• Descriptive survey: A type of survey research that describes the characteristics or attributes of a population or phenomenon, often used in exploratory research or to summarize existing data.
• Diagnostic survey: A type of survey research that assesses the current state or condition of an individual or system, often used in health or organizational research.
• Explanatory survey: A type of survey research that seeks to explain or understand the causes or mechanisms behind a phenomenon, often used in social or psychological research.
• Process evaluation survey: A type of survey research that measures the implementation and outcomes of a program or intervention, often used in program evaluation or quality improvement.
• Impact evaluation survey: A type of survey research that assesses the effectiveness or impact of a program or intervention, often used to inform policy or decision-making.
• Customer satisfaction survey: A type of survey research that measures the satisfaction or dissatisfaction of customers with a product, service, or experience, often used in marketing or customer service research.
• Market research survey: A type of survey research that collects data on consumer preferences, behaviors, or attitudes, often used in market research or product development.
• Public opinion survey: A type of survey research that measures the attitudes, beliefs, or opinions of a population on a specific issue or topic, often used in political or social research.
• Behavioral survey: A type of survey research that measures actual behavior or actions of individuals, often used in health or social research.
• Attitude survey: A type of survey research that measures the attitudes, beliefs, or opinions of individuals, often used in social or psychological research.
• Opinion poll: A type of survey research that measures the opinions or preferences of a population on a specific issue or topic, often used in political or media research.
• Ad hoc survey: A type of survey research that is conducted for a specific purpose or research question, often used in exploratory research or to answer a specific research question.

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

Quantitative survey research is a method of collecting numerical data from a sample of participants through the use of standardized surveys or questionnaires. The purpose of quantitative survey research is to gather empirical evidence that can be analyzed statistically to draw conclusions about a particular population or phenomenon.

In quantitative survey research, the questions are structured and pre-determined, often utilizing closed-ended questions, where participants are given a limited set of response options to choose from. This approach allows for efficient data collection and analysis, as well as the ability to generalize the findings to a larger population.

Quantitative survey research is often used in market research, social sciences, public health, and other fields where numerical data is needed to make informed decisions and recommendations.

Qualitative survey research is a method of collecting non-numerical data from a sample of participants through the use of open-ended questions or semi-structured interviews. The purpose of qualitative survey research is to gain a deeper understanding of the experiences, perceptions, and attitudes of participants towards a particular phenomenon or topic.

In qualitative survey research, the questions are open-ended, allowing participants to share their thoughts and experiences in their own words. This approach allows for a rich and nuanced understanding of the topic being studied, and can provide insights that are difficult to capture through quantitative methods alone.

Qualitative survey research is often used in social sciences, education, psychology, and other fields where a deeper understanding of human experiences and perceptions is needed to inform policy, practice, or theory.

Data Analysis Methods

There are several Survey Research Data Analysis Methods that researchers may use, including:

• Descriptive statistics: This method is used to summarize and describe the basic features of the survey data, such as the mean, median, mode, and standard deviation. These statistics can help researchers understand the distribution of responses and identify any trends or patterns.
• Inferential statistics: This method is used to make inferences about the larger population based on the data collected in the survey. Common inferential statistical methods include hypothesis testing, regression analysis, and correlation analysis.
• Factor analysis: This method is used to identify underlying factors or dimensions in the survey data. This can help researchers simplify the data and identify patterns and relationships that may not be immediately apparent.
• Cluster analysis: This method is used to group similar respondents together based on their survey responses. This can help researchers identify subgroups within the larger population and understand how different groups may differ in their attitudes, behaviors, or preferences.
• Structural equation modeling: This method is used to test complex relationships between variables in the survey data. It can help researchers understand how different variables may be related to one another and how they may influence one another.
• Content analysis: This method is used to analyze open-ended responses in the survey data. Researchers may use software to identify themes or categories in the responses, or they may manually review and code the responses.
• Text mining: This method is used to analyze text-based survey data, such as responses to open-ended questions. Researchers may use software to identify patterns and themes in the text, or they may manually review and code the text.

Applications of Survey Research

Here are some common applications of survey research:

• Market Research: Companies use survey research to gather insights about customer needs, preferences, and behavior. These insights are used to create marketing strategies and develop new products.
• Public Opinion Research: Governments and political parties use survey research to understand public opinion on various issues. This information is used to develop policies and make decisions.
• Social Research: Survey research is used in social research to study social trends, attitudes, and behavior. Researchers use survey data to explore topics such as education, health, and social inequality.
• Academic Research: Survey research is used in academic research to study various phenomena. Researchers use survey data to test theories, explore relationships between variables, and draw conclusions.
• Customer Satisfaction Research: Companies use survey research to gather information about customer satisfaction with their products and services. This information is used to improve customer experience and retention.
• Employee Surveys: Employers use survey research to gather feedback from employees about their job satisfaction, working conditions, and organizational culture. This information is used to improve employee retention and productivity.
• Health Research: Survey research is used in health research to study topics such as disease prevalence, health behaviors, and healthcare access. Researchers use survey data to develop interventions and improve healthcare outcomes.

Examples of Survey Research

Here are some real-time examples of survey research:

• COVID-19 Pandemic Surveys: Since the outbreak of the COVID-19 pandemic, surveys have been conducted to gather information about public attitudes, behaviors, and perceptions related to the pandemic. Governments and healthcare organizations have used this data to develop public health strategies and messaging.
• Political Polls During Elections: During election seasons, surveys are used to measure public opinion on political candidates, policies, and issues in real-time. This information is used by political parties to develop campaign strategies and make decisions.
• Customer Feedback Surveys: Companies often use real-time customer feedback surveys to gather insights about customer experience and satisfaction. This information is used to improve products and services quickly.
• Event Surveys: Organizers of events such as conferences and trade shows often use surveys to gather feedback from attendees in real-time. This information can be used to improve future events and make adjustments during the current event.
• Website and App Surveys: Website and app owners use surveys to gather real-time feedback from users about the functionality, user experience, and overall satisfaction with their platforms. This feedback can be used to improve the user experience and retain customers.
• Employee Pulse Surveys: Employers use real-time pulse surveys to gather feedback from employees about their work experience and overall job satisfaction. This feedback is used to make changes in real-time to improve employee retention and productivity.

Survey Sample

Purpose of survey research.

The purpose of survey research is to gather data and insights from a representative sample of individuals. Survey research allows researchers to collect data quickly and efficiently from a large number of people, making it a valuable tool for understanding attitudes, behaviors, and preferences.

Here are some common purposes of survey research:

• Descriptive Research: Survey research is often used to describe characteristics of a population or a phenomenon. For example, a survey could be used to describe the characteristics of a particular demographic group, such as age, gender, or income.
• Exploratory Research: Survey research can be used to explore new topics or areas of research. Exploratory surveys are often used to generate hypotheses or identify potential relationships between variables.
• Explanatory Research: Survey research can be used to explain relationships between variables. For example, a survey could be used to determine whether there is a relationship between educational attainment and income.
• Evaluation Research: Survey research can be used to evaluate the effectiveness of a program or intervention. For example, a survey could be used to evaluate the impact of a health education program on behavior change.
• Monitoring Research: Survey research can be used to monitor trends or changes over time. For example, a survey could be used to monitor changes in attitudes towards climate change or political candidates over time.

When to use Survey Research

there are certain circumstances where survey research is particularly appropriate. Here are some situations where survey research may be useful:

• When the research question involves attitudes, beliefs, or opinions: Survey research is particularly useful for understanding attitudes, beliefs, and opinions on a particular topic. For example, a survey could be used to understand public opinion on a political issue.
• When the research question involves behaviors or experiences: Survey research can also be useful for understanding behaviors and experiences. For example, a survey could be used to understand the prevalence of a particular health behavior.
• When a large sample size is needed: Survey research allows researchers to collect data from a large number of people quickly and efficiently. This makes it a useful method when a large sample size is needed to ensure statistical validity.
• When the research question is time-sensitive: Survey research can be conducted quickly, which makes it a useful method when the research question is time-sensitive. For example, a survey could be used to understand public opinion on a breaking news story.
• When the research question involves a geographically dispersed population: Survey research can be conducted online, which makes it a useful method when the population of interest is geographically dispersed.

How to Conduct Survey Research

Conducting survey research involves several steps that need to be carefully planned and executed. Here is a general overview of the process:

• Define the research question: The first step in conducting survey research is to clearly define the research question. The research question should be specific, measurable, and relevant to the population of interest.
• Develop a survey instrument : The next step is to develop a survey instrument. This can be done using various methods, such as online survey tools or paper surveys. The survey instrument should be designed to elicit the information needed to answer the research question, and should be pre-tested with a small sample of individuals.
• Select a sample : The sample is the group of individuals who will be invited to participate in the survey. The sample should be representative of the population of interest, and the size of the sample should be sufficient to ensure statistical validity.
• Administer the survey: The survey can be administered in various ways, such as online, by mail, or in person. The method of administration should be chosen based on the population of interest and the research question.
• Analyze the data: Once the survey data is collected, it needs to be analyzed. This involves summarizing the data using statistical methods, such as frequency distributions or regression analysis.
• Draw conclusions: The final step is to draw conclusions based on the data analysis. This involves interpreting the results and answering the research question.

Advantages of Survey Research

There are several advantages to using survey research, including:

• Efficient data collection: Survey research allows researchers to collect data quickly and efficiently from a large number of people. This makes it a useful method for gathering information on a wide range of topics.
• Standardized data collection: Surveys are typically standardized, which means that all participants receive the same questions in the same order. This ensures that the data collected is consistent and reliable.
• Cost-effective: Surveys can be conducted online, by mail, or in person, which makes them a cost-effective method of data collection.
• Anonymity: Participants can remain anonymous when responding to a survey. This can encourage participants to be more honest and open in their responses.
• Easy comparison: Surveys allow for easy comparison of data between different groups or over time. This makes it possible to identify trends and patterns in the data.
• Versatility: Surveys can be used to collect data on a wide range of topics, including attitudes, beliefs, behaviors, and preferences.

Limitations of Survey Research

Here are some of the main limitations of survey research:

• Limited depth: Surveys are typically designed to collect quantitative data, which means that they do not provide much depth or detail about people’s experiences or opinions. This can limit the insights that can be gained from the data.
• Potential for bias: Surveys can be affected by various biases, including selection bias, response bias, and social desirability bias. These biases can distort the results and make them less accurate.
• L imited validity: Surveys are only as valid as the questions they ask. If the questions are poorly designed or ambiguous, the results may not accurately reflect the respondents’ attitudes or behaviors.
• Limited generalizability : Survey results are only generalizable to the population from which the sample was drawn. If the sample is not representative of the population, the results may not be generalizable to the larger population.
• Limited ability to capture context: Surveys typically do not capture the context in which attitudes or behaviors occur. This can make it difficult to understand the reasons behind the responses.
• Limited ability to capture complex phenomena: Surveys are not well-suited to capture complex phenomena, such as emotions or the dynamics of interpersonal relationships.

Following is an example of a Survey Sample:

Welcome to our Survey Research Page! We value your opinions and appreciate your participation in this survey. Please answer the questions below as honestly and thoroughly as possible.

1. What is your age?

• A) Under 18
• G) 65 or older

2. What is your highest level of education completed?

• A) Less than high school
• B) High school or equivalent
• C) Some college or technical school
• D) Bachelor’s degree
• E) Graduate or professional degree

3. What is your current employment status?

• A) Employed full-time
• B) Employed part-time
• C) Self-employed
• D) Unemployed

4. How often do you use the internet per day?

•  A) Less than 1 hour
• B) 1-3 hours
• C) 3-5 hours
• D) 5-7 hours
• E) More than 7 hours

5. How often do you engage in social media per day?

6. Have you ever participated in a survey research study before?

7. If you have participated in a survey research study before, how was your experience?

• A) Excellent
• E) Very poor

8. What are some of the topics that you would be interested in participating in a survey research study about?

……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….

9. How often would you be willing to participate in survey research studies?

• A) Once a week
• B) Once a month
• C) Once every 6 months
• D) Once a year

10. Any additional comments or suggestions?

Thank you for taking the time to complete this survey. Your feedback is important to us and will help us improve our survey research efforts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to make a survey report: A guide to analyzing and detailing insights

• March 8, 2024

The survey report: Meaning and importance

Survey findings, analysis and interpretation, recommendations, use clear and accessible language, structure a report for clarity, provide context, include visual aids, cite sources, proofread and edit, introduction, create a survey with surveyplanet.

In today’s data-driven world, surveys are indispensable tools for gathering valuable intelligence and making informed decisions. Whether conducting market research, gauging customer satisfaction, or gathering employee feedback, the key to unlocking a survey’s true potential lies in the subsequent analysis and reporting of the collected data.

Whether you’re new to surveys or a seasoned researcher, mastering analysis and reporting is essential. To unlock the full potential of surveys one must learn how to make a survey report.

Before diving into the process, let’s clarify what a survey report is and why it’s crucial. It is a structured document that presents the findings, analysis, and conclusions derived from survey data. It serves as a means to communicate the insights obtained from the survey to stakeholders, enabling them to make informed decisions.

The importance of a survey report cannot be overstated. It provides a comprehensive overview of collected data, allowing stakeholders to gain a deeper understanding of the subject matter. Additionally, it serves as a reference point for future decision-making and strategy development, ensuring that actions are based on sound evidence rather than assumptions.

Key components of a survey report

Start a survey report with a brief overview of the purpose of the survey, its objectives, and the methodology used for data collection. This sets the context for the rest of the report and helps readers understand the scope of the survey.

The introduction serves as the roadmap that guides readers through the document and provides essential background information. It should answer questions such as why the survey was conducted, who the target audience was, and how the data was collected . By setting clear expectations upfront, the groundwork is laid for a coherent and compelling report.

Present the key findings of the survey in a clear and organized manner. Use charts, graphs, and tables to visualize the data effectively. Ensure that the findings are presented in a logical sequence, making it easy for readers to follow the narrative.

The survey findings section is the heart of the report, where the raw data collected during the survey is presented. It’s essential to organize the findings in a way that is easy to understand and digest. Visual aids such as charts, graphs, and tables can help illustrate trends and patterns in the data, making it easier for readers to grasp the key insights.

Dive deeper into the survey data by analyzing trends, patterns, and correlations. Provide insights into what the data means and why certain trends may be occurring. The findings must be interpreted in the context of the survey’s objectives and any relevant background information.

Analysis and interpretation are where the real value of the survey report lies. This is where surface-level findings are moved beyond to uncover the underlying meaning behind the data. By digging deeper to provide meaningful insights, stakeholders gain a deeper understanding of the issues at hand and identify potential opportunities for action.

Based on the analysis, offer actionable recommendations or suggestions that address the issues identified in the survey. These recommendations should be practical, feasible, and tied directly to the survey findings.

The recommendations section is where insights are translated into action. It’s not enough to simply present the findings—clear guidance on what steps should be taken next must be provided. Recommendations should be specific, actionable, and backed by evidence from the survey data. Such practical guidance empowers stakeholders to make informed decisions that drive positive change.

Don’t forget to summarize the key findings, insights, and recommendations presented in the report. Reinforce the importance of the survey results and emphasize how they can be used to drive decision-making.

The conclusion serves as a final wrap-up, summarizing the key takeaways and reinforcing the importance of the findings. It’s an opportunity to remind stakeholders of the survey’s value and how the results can be used to inform decision-making and drive positive change. By ending on a strong note, readers have a clear understanding of the significance of the survey and the actions that need to be taken moving forward.

Best practices for survey report writing

In addition to understanding the key components of a survey report, it’s essential to follow best practices when writing and presenting findings. Here are some tips to ensure that a survey report is clear, concise, and impactful.

Avoid technical jargon or overly complex language that may confuse readers. Instead, use clear and straightforward wording that is easily understood by the target audience.

Organize a survey report into clearly defined sections:

• Conclusion.

This helps readers navigate the document and find needed information quickly.

Always provide the background of findings by explaining the significance of the survey objectives and how the data relates to the broader goals of the organization or project.

Charts, graphs, and tables can help illustrate key findings and trends in the data. Use them sparingly and ensure they are properly labeled and explained in the text.

When referencing external sources or previous research, be sure to cite them properly. This adds credibility to the findings and allows readers to explore the topic further if they wish.

Before finalizing a survey report, take the time to proofread and edit it for grammar, spelling, and formatting errors. A polished and professional-looking report reflects positively on your work and enhances its credibility.

By following these best practices, it is ensured that a survey report effectively communicates findings and insights to stakeholders, empowering them to make informed decisions based on the data collected.

Short survey report example

To illustrate the process, let’s consider a hypothetical short survey report example:

The purpose of this survey was to gather feedback from customers regarding their satisfaction with our products and services. The survey was conducted online and received responses from 300 participants over a two-week period.

• 85% of respondents reported being satisfied with the quality of our products.
• 70% indicated that they found our customer service to be responsive and helpful.
• The majority of respondents cited price as the primary factor influencing their purchasing decisions.

The high satisfaction ratings suggest that our products meet the expectations of our customers. However, the feedback regarding pricing indicates a potential area for improvement. By analyzing the data further, we can identify opportunities to adjust pricing strategies or offer discounts to better meet customer needs.

Based on the survey findings, we recommend conducting further market research to better understand pricing dynamics and competitive positioning. Additionally, we propose exploring initiatives to enhance the overall value proposition for our products and services.

The survey results provide valuable insights into customer perceptions and preferences. By acting on these findings, we can strengthen our competitive position and drive greater customer satisfaction and loyalty .

Creating a survey report involves more than just presenting data; it requires careful analysis, interpretation, and meaningful recommendations. By following the steps outlined in this guide and utilizing the survey report example like the one provided, you can effectively communicate survey findings and empower decision-makers to take action based on valuable insights.

Ready to turn survey insights into actionable results? Try SurveyPlanet, our powerful survey tool designed to streamline survey creation, data collection, and analysis. Sign up now for a free trial and experience the ease and efficiency of gathering valuable feedback with SurveyPlanet. Your journey to informed decision-making starts here!

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• Knowledge Base
• Methodology
• Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyse the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research: Investigating the experiences and characteristics of different social groups
• Market research: Finding out what customers think about products, services, and companies
• Health research: Collecting data from patients about symptoms and treatments
• Politics: Measuring public opinion about parties and policies
• Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• University students in the UK
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18 to 24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
• An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g., residents of a specific region).
• The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyse.
• The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g., yes/no or agree/disagree )
• A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g., age categories)
• A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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Chapter 9: Survey Research

Overview of Survey Research

Learning Objectives

• Define what survey research is, including its two important characteristics.
• Describe several different ways that survey research can be used and give some examples.

What Is Survey Research?

Survey research  is a quantitative and qualitative method with two important characteristics. First, the variables of interest are measured using self-reports. In essence, survey researchers ask their participants (who are often called respondents  in survey research) to report directly on their own thoughts, feelings, and behaviours. Second, considerable attention is paid to the issue of sampling. In particular, survey researchers have a strong preference for large random samples because they provide the most accurate estimates of what is true in the population. In fact, survey research may be the only approach in psychology in which random sampling is routinely used. Beyond these two characteristics, almost anything goes in survey research. Surveys can be long or short. They can be conducted in person, by telephone, through the mail, or over the Internet. They can be about voting intentions, consumer preferences, social attitudes, health, or anything else that it is possible to ask people about and receive meaningful answers.  Although survey data are often analyzed using statistics, there are many questions that lend themselves to more qualitative analysis.

Most survey research is nonexperimental. It is used to describe single variables (e.g., the percentage of voters who prefer one presidential candidate or another, the prevalence of schizophrenia in the general population) and also to assess statistical relationships between variables (e.g., the relationship between income and health). But surveys can also be experimental. The study by Lerner and her colleagues is a good example. Their use of self-report measures and a large national sample identifies their work as survey research. But their manipulation of an independent variable (anger vs. fear) to assess its effect on a dependent variable (risk judgments) also identifies their work as experimental.

History and Uses of Survey Research

Survey research may have its roots in English and American “social surveys” conducted around the turn of the 20th century by researchers and reformers who wanted to document the extent of social problems such as poverty (Converse, 1987) [1] . By the 1930s, the US government was conducting surveys to document economic and social conditions in the country. The need to draw conclusions about the entire population helped spur advances in sampling procedures. At about the same time, several researchers who had already made a name for themselves in market research, studying consumer preferences for American businesses, turned their attention to election polling. A watershed event was the presidential election of 1936 between Alf Landon and Franklin Roosevelt. A magazine called  Literary Digest  conducted a survey by sending ballots (which were also subscription requests) to millions of Americans. Based on this “straw poll,” the editors predicted that Landon would win in a landslide. At the same time, the new pollsters were using scientific methods with much smaller samples to predict just the opposite—that Roosevelt would win in a landslide. In fact, one of them, George Gallup, publicly criticized the methods of Literary Digest  before the election and all but guaranteed that his prediction would be correct. And of course it was. (We will consider the reasons that Gallup was right later in this chapter.) Interest in surveying around election times has led to several long-term projects, notably the Canadian Election Studies which has measured opinions of Canadian voters around federal elections since 1965.  Anyone can access the data and read about the results of the experiments in these studies.

From market research and election polling, survey research made its way into several academic fields, including political science, sociology, and public health—where it continues to be one of the primary approaches to collecting new data. Beginning in the 1930s, psychologists made important advances in questionnaire design, including techniques that are still used today, such as the Likert scale. (See “What Is a Likert Scale?” in  Section 9.2 “Constructing Survey Questionnaires” .) Survey research has a strong historical association with the social psychological study of attitudes, stereotypes, and prejudice. Early attitude researchers were also among the first psychologists to seek larger and more diverse samples than the convenience samples of university students that were routinely used in psychology (and still are).

Survey research continues to be important in psychology today. For example, survey data have been instrumental in estimating the prevalence of various mental disorders and identifying statistical relationships among those disorders and with various other factors. The National Comorbidity Survey is a large-scale mental health survey conducted in the United States . In just one part of this survey, nearly 10,000 adults were given a structured mental health interview in their homes in 2002 and 2003.  Table 9.1  presents results on the lifetime prevalence of some anxiety, mood, and substance use disorders. (Lifetime prevalence is the percentage of the population that develops the problem sometime in their lifetime.) Obviously, this kind of information can be of great use both to basic researchers seeking to understand the causes and correlates of mental disorders as well as to clinicians and policymakers who need to understand exactly how common these disorders are.

And as the opening example makes clear, survey research can even be used to conduct experiments to test specific hypotheses about causal relationships between variables. Such studies, when conducted on large and diverse samples, can be a useful supplement to laboratory studies conducted on university students. Although this approach is not a typical use of survey research, it certainly illustrates the flexibility of this method.

Key Takeaways

• Survey research is a quantitative approach that features the use of self-report measures on carefully selected samples. It is a flexible approach that can be used to study a wide variety of basic and applied research questions.
• Survey research has its roots in applied social research, market research, and election polling. It has since become an important approach in many academic disciplines, including political science, sociology, public health, and, of course, psychology.

Discussion: Think of a question that each of the following professionals might try to answer using survey research.

• a social psychologist
• an educational researcher
• a market researcher who works for a supermarket chain
• the mayor of a large city
• the head of a university police force
• Converse, J. M. (1987). Survey research in the United States: Roots and emergence, 1890–1960 . Berkeley, CA: University of California Press. ↵
• The lifetime prevalence of a disorder is the percentage of people in the population that develop that disorder at any time in their lives. ↵

A quantitative approach in which variables are measured using self-reports from a sample of the population.

Participants of a survey.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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9.1 Overview of Survey Research

Learning objectives.

• Define what survey research is, including its two important characteristics.
• Describe several different ways that survey research can be used and give some examples.

What Is Survey Research?

Survey research is a quantitative approach that has two important characteristics. First, the variables of interest are measured using self-reports. In essence, survey researchers ask their participants (who are often called respondents in survey research) to report directly on their own thoughts, feelings, and behaviors. Second, considerable attention is paid to the issue of sampling. In particular, survey researchers have a strong preference for large random samples because they provide the most accurate estimates of what is true in the population. In fact, survey research may be the only approach in psychology in which random sampling is routinely used. Beyond these two characteristics, almost anything goes in survey research. Surveys can be long or short. They can be conducted in person, by telephone, through the mail, or over the Internet. They can be about voting intentions, consumer preferences, social attitudes, health, or anything else that it is possible to ask people about and receive meaningful answers.

Most survey research is nonexperimental. It is used to describe single variables (e.g., the percentage of voters who prefer one presidential candidate or another, the prevalence of schizophrenia in the general population) and also to assess statistical relationships between variables (e.g., the relationship between income and health). But surveys can also be experimental. The study by Lerner and her colleagues is a good example. Their use of self-report measures and a large national sample identifies their work as survey research. But their manipulation of an independent variable (anger vs. fear) to assess its effect on a dependent variable (risk judgments) also identifies their work as experimental.

History and Uses of Survey Research

Survey research may have its roots in English and American “social surveys” conducted around the turn of the 20th century by researchers and reformers who wanted to document the extent of social problems such as poverty (Converse, 1987). By the 1930s, the US government was conducting surveys to document economic and social conditions in the country. The need to draw conclusions about the entire population helped spur advances in sampling procedures. At about the same time, several researchers who had already made a name for themselves in market research, studying consumer preferences for American businesses, turned their attention to election polling. A watershed event was the presidential election of 1936 between Alf Landon and Franklin Roosevelt. A magazine called Literary Digest conducted a survey by sending ballots (which were also subscription requests) to millions of Americans. Based on this “straw poll,” the editors predicted that Landon would win in a landslide. At the same time, the new pollsters were using scientific methods with much smaller samples to predict just the opposite—that Roosevelt would win in a landslide. In fact, one of them, George Gallup, publicly criticized the methods of Literary Digest before the election and all but guaranteed that his prediction would be correct. And of course it was. (We will consider the reasons that Gallup was right later in this chapter.)

From market research and election polling, survey research made its way into several academic fields, including political science, sociology, and public health—where it continues to be one of the primary approaches to collecting new data. Beginning in the 1930s, psychologists made important advances in questionnaire design, including techniques that are still used today, such as the Likert scale. (See “What Is a Likert Scale?” in Section 9.2 “Constructing Survey Questionnaires” .) Survey research has a strong historical association with the social psychological study of attitudes, stereotypes, and prejudice. Early attitude researchers were also among the first psychologists to seek larger and more diverse samples than the convenience samples of college students that were routinely used in psychology (and still are).

Survey research continues to be important in psychology today. For example, survey data have been instrumental in estimating the prevalence of various mental disorders and identifying statistical relationships among those disorders and with various other factors. The National Comorbidity Survey is a large-scale mental health survey conducted in the United States (see http://www.hcp.med.harvard.edu/ncs ). In just one part of this survey, nearly 10,000 adults were given a structured mental health interview in their homes in 2002 and 2003. Table 9.1 “Some Lifetime Prevalence Results From the National Comorbidity Survey” presents results on the lifetime prevalence of some anxiety, mood, and substance use disorders. (Lifetime prevalence is the percentage of the population that develops the problem sometime in their lifetime.) Obviously, this kind of information can be of great use both to basic researchers seeking to understand the causes and correlates of mental disorders and also to clinicians and policymakers who need to understand exactly how common these disorders are.

Table 9.1 Some Lifetime Prevalence Results From the National Comorbidity Survey

And as the opening example makes clear, survey research can even be used to conduct experiments to test specific hypotheses about causal relationships between variables. Such studies, when conducted on large and diverse samples, can be a useful supplement to laboratory studies conducted on college students. Although this is not a typical use of survey research, it certainly illustrates the flexibility of this approach.

Key Takeaways

• Survey research is a quantitative approach that features the use of self-report measures on carefully selected samples. It is a flexible approach that can be used to study a wide variety of basic and applied research questions.
• Survey research has its roots in applied social research, market research, and election polling. It has since become an important approach in many academic disciplines, including political science, sociology, public health, and, of course, psychology.

Discussion: Think of a question that each of the following professionals might try to answer using survey research.

• a social psychologist
• an educational researcher
• a market researcher who works for a supermarket chain
• the mayor of a large city
• the head of a university police force

Converse, J. M. (1987). Survey research in the United States: Roots and emergence, 1890–1960 . Berkeley, CA: University of California Press.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

A Comprehensive Guide to Survey Research Methodologies

For decades, researchers and businesses have used survey research to produce statistical data and explore ideas. The survey process is simple, ask questions and analyze the responses to make decisions. Data is what makes the difference between a valid and invalid statement and as the American statistician, W. Edwards Deming said:

“Without data, you’re just another person with an opinion.” - W. Edwards Deming

In this article, we will discuss what survey research is, its brief history, types, common uses, benefits, and the step-by-step process of designing a survey.

What is Survey Research

A survey is a research method that is used to collect data from a group of respondents in order to gain insights and information regarding a particular subject. It’s an excellent method to gather opinions and understand how and why people feel a certain way about different situations and contexts.

Brief History of Survey Research

Survey research may have its roots in the American and English “social surveys” conducted around the turn of the 20th century. The surveys were mainly conducted by researchers and reformers to document the extent of social issues such as poverty. ( 1 ) Despite being a relatively young field to many scientific domains, survey research has experienced three stages of development ( 2 ):

-       First Era (1930-1960)

-       Second Era (1960-1990)

-       Third Era (1990 onwards)

Over the years, survey research adapted to the changing times and technologies. By exploiting the latest technologies, researchers can gain access to the right population from anywhere in the world, analyze the data like never before, and extract useful information.

Survey Research Methods & Types

Survey research can be classified into seven categories based on objective, data sources, methodology, deployment method, and frequency of deployment.

Surveys based on Objective

Exploratory survey research.

Exploratory survey research is aimed at diving deeper into research subjects and finding out more about their context. It’s important for marketing or business strategy and the focus is to discover ideas and insights instead of gathering statistical data.

Generally, exploratory survey research is composed of open-ended questions that allow respondents to express their thoughts and perspectives. The final responses present information from various sources that can lead to fresh initiatives.

Predictive Survey Research

Predictive survey research is also called causal survey research. It’s preplanned, structured, and quantitative in nature. It’s often referred to as conclusive research as it tries to explain the cause-and-effect relationship between different variables. The objective is to understand which variables are causes and which are effects and the nature of the relationship between both variables.

Descriptive Survey Research

Descriptive survey research is largely observational and is ideal for gathering numeric data. Due to its quantitative nature, it’s often compared to exploratory survey research. The difference between the two is that descriptive research is structured and pre-planned.

 The idea behind descriptive research is to describe the mindset and opinion of a particular group of people on a given subject. The questions are every day multiple choices and users must choose from predefined categories. With predefined choices, you don’t get unique insights, rather, statistically inferable data.

Survey Research Types based on Concept Testing

Monadic concept testing.

Monadic testing is a survey research methodology in which the respondents are split into multiple groups and ask each group questions about a separate concept in isolation. Generally, monadic surveys are hyper-focused on a particular concept and shorter in duration. The important thing in monadic surveys is to avoid getting off-topic or exhausting the respondents with too many questions.

Sequential Monadic Concept Testing

Another approach to monadic testing is sequential monadic testing. In sequential monadic surveys, groups of respondents are surveyed in isolation. However, instead of surveying three groups on three different concepts, the researchers survey the same groups of people on three distinct concepts one after another. In a sequential monadic survey, at least two topics are included (in random order), and the same questions are asked for each concept to eliminate bias.

Based on Data Source

Primary data.

Data obtained directly from the source or target population is referred to as primary survey data. When it comes to primary data collection, researchers usually devise a set of questions and invite people with knowledge of the subject to respond. The main sources of primary data are interviews, questionnaires, surveys, and observation methods.

 Compared to secondary data, primary data is gathered from first-hand sources and is more reliable. However, the process of primary data collection is both costly and time-consuming.

Secondary Data

Survey research is generally used to collect first-hand information from a respondent. However, surveys can also be designed to collect and process secondary data. It’s collected from third-party sources or primary sources in the past.

 This type of data is usually generic, readily available, and cheaper than primary data collection. Some common sources of secondary data are books, data collected from older surveys, online data, and data from government archives. Beware that you might compromise the validity of your findings if you end up with irrelevant or inflated data.

Based on Research Method

Quantitative research.

Quantitative research is a popular research methodology that is used to collect numeric data in a systematic investigation. It’s frequently used in research contexts where statistical data is required, such as sciences or social sciences. Quantitative research methods include polls, systematic observations, and face-to-face interviews.

Qualitative Research

Qualitative research is a research methodology where you collect non-numeric data from research participants. In this context, the participants are not restricted to a specific system and provide open-ended information. Some common qualitative research methods include focus groups, one-on-one interviews, observations, and case studies.

Based on Deployment Method

Online surveys.

With technology advancing rapidly, the most popular method of survey research is an online survey. With the internet, you can not only reach a broader audience but also design and customize a survey and deploy it from anywhere. Online surveys have outperformed offline survey methods as they are less expensive and allow researchers to easily collect and analyze data from a large sample.

Paper or Print Surveys

As the name suggests, paper or print surveys use the traditional paper and pencil approach to collect data. Before the invention of computers, paper surveys were the survey method of choice.

Though many would assume that surveys are no longer conducted on paper, it's still a reliable method of collecting information during field research and data collection. However, unlike online surveys, paper surveys are expensive and require extra human resources.

Telephonic Surveys

Telephonic surveys are conducted over telephones where a researcher asks a series of questions to the respondent on the other end. Contacting respondents over a telephone requires less effort, human resources, and is less expensive.

What makes telephonic surveys debatable is that people are often reluctant in giving information over a phone call. Additionally, the success of such surveys depends largely on whether people are willing to invest their time on a phone call answering questions.

One-on-one Surveys

One-on-one surveys also known as face-to-face surveys are interviews where the researcher and respondent. Interacting directly with the respondent introduces the human factor into the survey.

Face-to-face interviews are useful when the researcher wants to discuss something personal with the respondent. The response rates in such surveys are always higher as the interview is being conducted in person. However, these surveys are quite expensive and the success of these depends on the knowledge and experience of the researcher.

Based on Distribution

The easiest and most common way of conducting online surveys is sending out an email. Sending out surveys via emails has a higher response rate as your target audience already knows about your brand and is likely to engage.

Buy Survey Responses

Purchasing survey responses also yields higher responses as the responders signed up for the survey. Businesses often purchase survey samples to conduct extensive research. Here, the target audience is often pre-screened to check if they're qualified to take part in the research.

Embedding Survey on a Website

Embedding surveys on a website is another excellent way to collect information. It allows your website visitors to take part in a survey without ever leaving the website and can be done while a person is entering or exiting the website.

Post the Survey on Social Media

Social media is an excellent medium to reach abroad range of audiences. You can publish your survey as a link on social media and people who are following the brand can take part and answer questions.

Based on Frequency of Deployment

Cross-sectional studies.

Cross-sectional studies are administered to a small sample from a large population within a short period of time. This provides researchers a peek into what the respondents are thinking at a given time. The surveys are usually short, precise, and specific to a particular situation.

Longitudinal Surveys

Longitudinal surveys are an extension of cross-sectional studies where researchers make an observation and collect data over extended periods of time. This type of survey can be further divided into three types:

-       Trend surveys are employed to allow researchers to understand the change in the thought process of the respondents over some time.

-       Panel surveys are administered to the same group of people over multiple years. These are usually expensive and researchers must stick to their panel to gather unbiased opinions.

-       In cohort surveys, researchers identify a specific category of people and regularly survey them. Unlike panel surveys, the same people do not need to take part over the years, but each individual must fall into the researcher’s primary interest category.

Retrospective Survey

Retrospective surveys allow researchers to ask questions to gather data about past events and beliefs of the respondents. Since retrospective surveys also require years of data, they are similar to the longitudinal survey, except retrospective surveys are shorter and less expensive.

Why Should You Conduct Research Surveys?

“In God we trust. All others must bring data” - W. Edwards Deming

 In the information age, survey research is of utmost importance and essential for understanding the opinion of your target population. Whether you’re launching a new product or conducting a social survey, the tool can be used to collect specific information from a defined set of respondents. The data collected via surveys can be further used by organizations to make informed decisions.

Furthermore, compared to other research methods, surveys are relatively inexpensive even if you’re giving out incentives. Compared to the older methods such as telephonic or paper surveys, online surveys have a smaller cost and the number of responses is higher.

 What makes surveys useful is that they describe the characteristics of a large population. With a larger sample size , you can rely on getting more accurate results. However, you also need honest and open answers for accurate results. Since surveys are also anonymous and the responses remain confidential, respondents provide candid and accurate answers.

Common Uses of a Survey

Surveys are widely used in many sectors, but the most common uses of the survey research include:

-       Market research : surveying a potential market to understand customer needs, preferences, and market demand.

-       Customer Satisfaction: finding out your customer’s opinions about your services, products, or companies .

-       Social research: investigating the characteristics and experiences of various social groups.

-       Health research: collecting data about patients’ symptoms and treatments.

-       Politics: evaluating public opinion regarding policies and political parties.

-       Psychology: exploring personality traits, behaviors, and preferences.

6 Steps to Conduct Survey Research

An organization, person, or company conducts a survey when they need the information to make a decision but have insufficient data on hand. Following are six simple steps that can help you design a great survey.

Step 1: Objective of the Survey

The first step in survey research is defining an objective. The objective helps you define your target population and samples. The target population is the specific group of people you want to collect data from and since it’s rarely possible to survey the entire population, we target a specific sample from it. Defining a survey objective also benefits your respondents by helping them understand the reason behind the survey.

Step 2: Number of Questions

The number of questions or the size of the survey depends on the survey objective. However, it’s important to ensure that there are no redundant queries and the questions are in a logical order. Rephrased and repeated questions in a survey are almost as frustrating as in real life. For a higher completion rate, keep the questionnaire small so that the respondents stay engaged to the very end. The ideal length of an interview is less than 15 minutes. ( 2 )

Step 3: Language and Voice of Questions

While designing a survey, you may feel compelled to use fancy language. However, remember that difficult language is associated with higher survey dropout rates. You need to speak to the respondent in a clear, concise, and neutral manner, and ask simple questions. If your survey respondents are bilingual, then adding an option to translate your questions into another language can also prove beneficial.

Step 4: Type of Questions

In a survey, you can include any type of questions and even both closed-ended or open-ended questions. However, opt for the question types that are the easiest to understand for the respondents, and offer the most value. For example, compared to open-ended questions, people prefer to answer close-ended questions such as MCQs (multiple choice questions)and NPS (net promoter score) questions.

Step 5: User Experience

Designing a great survey is about more than just questions. A lot of researchers underestimate the importance of user experience and how it affects their response and completion rates. An inconsistent, difficult-to-navigate survey with technical errors and poor color choice is unappealing for the respondents. Make sure that your survey is easy to navigate for everyone and if you’re using rating scales, they remain consistent throughout the research study.

Additionally, don’t forget to design a good survey experience for both mobile and desktop users. According to Pew Research Center, nearly half of the smartphone users access the internet mainly from their mobile phones and 14 percent of American adults are smartphone-only internet users. ( 3 )

Step 6: Survey Logic

Last but not least, logic is another critical aspect of the survey design. If the survey logic is flawed, respondents may not continue in the right direction. Make sure to test the logic to ensure that selecting one answer leads to the next logical question instead of a series of unrelated queries.

How to Effectively Use Survey Research with Starlight Analytics

Designing and conducting a survey is almost as much science as it is an art. To craft great survey research, you need technical skills, consider the psychological elements, and have a broad understanding of marketing.

The ultimate goal of the survey is to ask the right questions in the right manner to acquire the right results.

Bringing a new product to the market is a long process and requires a lot of research and analysis. In your journey to gather information or ideas for your business, Starlight Analytics can be an excellent guide. Starlight Analytics' product concept testing helps you measure your product's market demand and refine product features and benefits so you can launch with confidence. The process starts with custom research to design the survey according to your needs, execute the survey, and deliver the key insights on time.

• Survey research in the United States: roots and emergence, 1890-1960 https://searchworks.stanford.edu/view/10733873    
• How to create a survey questionnaire that gets great responses https://luc.id/knowledgehub/how-to-create-a-survey-questionnaire-that-gets-great-responses/    
• Internet/broadband fact sheet https://www.pewresearch.org/internet/fact-sheet/internet-broadband/    

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The Hidden Reason Why Market Research Matters

While there are many self-evident reasons why market research matters, they all tend to center around one hidden reason: your intuition is not always right. By recognizing these implicit biases, and regularly challenging your intuition, you open yourself up to new business opportunities, and insights about your market + customers that run counter to your gut.

Survey Report: What is it & How to Create it?

So, you’ve conducted a survey and came up with strategies to get the most responses to that survey.

A survey does not end after you managed to capture a lot of responses. Responses are just plain data.

A survey report is how you convert that data into information and implement the results in your research.

Data left unanalyzed is just a mess of numbers and words, which do no good to anyone.In this article, we’ll show you the ins and outs of writing a fantastic survey report.

Before getting into the step-by-step process, let’s first understand what survey reports are.

What is a Survey Report? (Definition)

A survey report is a document that demonstrates all the important information about the survey in an objective, clear, precise, and fact-based manner.

The report defines the:

• The objective of the survey
• Number of questions
• Number of respondents
• Start and end date of the survey
• The demographics of the people who have answered (geographical area, gender, age, marital status, etc)
• Your findings and conclusion from the given data

All this data should be presented using graphs, charts, and tables. Anything that makes the data easy-to-read and understand.

After reading your survey report, the reader should be clear on:

• Why you conducted this survey.
• The time period the survey ran.
• Channels used to promote and fill up the survey.
• Demographics of the respondents.
• What you found out after conducting the survey.
• How can the findings be implemented to create better results?

Importance of Writing a Survey Report

Here are four compelling reasons why you should always write a survey report:

1. Make a powerful impact

Survey reports reveal the hard numbers regarding a scenario. It is always impactful when you include stats with facts.

For instance, saying “80% of women working in the media sector claim to have faced workplace harassment at some time in their life” is more impactful than saying “Many women face workplace harassment.”

Data is much more powerful when we know the exact proportion of it. People connect with issues that come with large numbers, as they stir up the room and demand for action.

Read more:   How To Create A Customer Survey For Better Insights?

2. Paves the way for d ecision making

When you categorize large data into easy to read charts and graphs, it gets converted into useful information. This information is then used by the management to make decisions that will directly affect the company.

For example, let’s say that you performed a product feedback survey to find out the preferences of your target audience.

Based on their answers, the features of your product can be amended.

After all, it’s the people for whom you are making the product, right?

3. Trend is your friend

This is a common saying among surveyors and researchers. It implies that when you ask one question again and again over time, you find a trend of change in the answers.

Thus, survey reports help track trends in the market that also provides insight into what the future could hold.

For instance, if we talk about fashion, bell-bottom jeans were a huge trend in the ’70s. Then, the ’80s saw carrot pants followed by ankle-high skinny jeans in the 90s.

Fashion researchers track these changes and bring back some of the old trends. Bell-bottoms and carrot pants came back and Gen Z is loving it!

4. Helps to gather explicit data

Explicit data in survey terms means first-hand data that is obtained without any tampering in the process. Data often gets contaminated, when it is not received first-hand and transfers through various mediums.

Survey reports help express information fully and clearly without beating around the bush. However, the possibility of a respondent altering the data, lying, or manipulating should be considered.

First-hand data should not be blindly followed. It must be supported by some underlying facts.

With this thought in mind, let’s move to the actual steps required to write a survey report.

Read more:   Formal Reports: What are they & How to Create them!

How to Write a Survey Report in 5 Easy Steps?

If you are here trying to learn how to make a survey report, we can assume that you have already taken two steps:

• Created & distributed a questionnaire/survey
• Received responses to it

When its time to analyze the collected data, take the following steps:

Step 1: Export Data

Whether you used Google Forms, Typeform, Survey Monkey, or any other survey platform, the result of the survey conducted comes in two ways. One is a spreadsheet document filled with data and the other is the graphical and chart representation of the data.

Export this real-time information in your survey report by either downloading, printing, or simply copy-pasting the graphical results of the survey into your survey report document.

This legitimates your survey and lets the reader see the exact survey you conducted and its digital results without any edits or data manipulation.

Read more:  How to Embed Google Form to Your Documents?

Step 2: Filter, Analyze and Visualize

The next step is to filter the data. You’ll want to look out for corrupt, biased, duplicate, or inaccurate information and filter it out. This step is also called cleaning the data. The cleaned data is then analyzed to infer results.

Analyzing the data includes grouping similar aspects, categorizing, and identifying patterns.

For instance, XYZ company conducted an employee satisfaction survey.

In it, they asked, how is the relationship between you and your immediate supervisor?

According to the data, it is found that 80% workforce said that their supervisor was warm and friendly. the other 20% gave a mixed kind of response.

On analyzing it, it was determined that most of the workforce helps each other and the pyramid of command is running successfully.

So the XYZ company will group this information and present it like: ‘4 out of 5 employees working in XYZ organization claimed to have a warm and friendly relationship with their supervisor ‘

With this, it can be concluded that the work environment of XYZ organization is good. They will also use this information to attract more workforce towards the organization.

It is always better to put the information in statistical terms. This makes the visualization process easier. While visualizing, you collect the analyzed data in the form of easily understandable charts, graphs, or figures.

Visualization makes the data go alive!

Step 3: Interpret Data

At this point, you have all your information ready and baked. It time to eat!

By eating, we mean inferring what you found out from the collected data. Observe your findings with supporting facts and figures and also think about the next step/recommendations to make a change.

But hey, we can’t eat before presenting the dishes first. Presentation is an important element!

However, not every survey report is presented the same way. This leads us to the next step…

Step 4: Recognise the Type of Survey Report

There are various kinds of survey reports, depending on the nature and objective of the survey. Recognize what type your survey falls into. Some common ones include:

• Employee Satisfaction Survey: This is done to determine the opinion of the employees regarding the workspace. It helps in increasing employee motivation and makes them feel heard.
• Customer Satisfaction Survey: You must have come across one of these in your life. Many restaurants, salons, companies ask their customers to fill out a form giving feedback.
• Market Research Survey: This type of survey is performed to find out the preferences and demographics of the target audience. It also helps with competitor research.
• Social Survey: This is a survey conducted to find out stats about social topics such as climate change, waste management, poverty, etc.

Step 5: Structure of the Survey Report

Add the title of your survey, name of the organization, date of submission, name of the mentor, etc.

• Background and Objective

Provide a background of the topic at hand, giving insight as to why this survey is conducted. The reason behind it is known as the objective of the report.

• Methodology

Your methodology should tell the readers about the methods you used to conduct the survey, channels used to spread it, and the ways used to analyze the received data.

The conclusion should contain a detailed picture of your findings. It includes listing what you determined by the survey in form of facts, figures, and statistics.

• Recommendation

Give the reader the next step or CTA (call to action) in your survey report. After sharing the survey and analyzing the results, offer some insightful recommendations to make a change, amend or implicate something.

For instance, to improve employee satisfaction and communication, we can hold a weekly town hall meeting.

Include detailed information that is too long/complicated to put in the report but is used or referred to in the report. It may include long mathematical calculations, tables of raw data, in-depth charts, etc.

Make sure to properly credit every source that you extracted information from. This is very important as the absence of references puts a threat of plagiarism in your report.

• Table of Contents

Usually, it is included at the beginning of any report or project. However, in the case of the survey report, the table of contents comes at the end. It lists everything present in the report divided into sections and sub-sections.

• Executive Summary

It is a crucial element of your report. Not everybody has the time to go through the entire survey report. The executive summary should be able to summarise the whole survey in one or two pages.

Okay great so now you know how to write a Survey Report, how about we show you the smartest & fastest way for you to create yours?

Bit.ai : The Ultimate Tool for Creating Survey Reports

Easily weave any type of digital content within your Bit docs like file attachments, visual web links, cloud files , PDF previews, math equations, videos , and much more. Bit integrates across 80+ popular applications like Google Sheets , OneDrive , Tableau , Typeform , Lucidcharts , and much more! Now your content, wherever it may reside can part of your survey report.

Bit’s impressive editor is collaborative so that you can work with your team at the same time and create smart documents that help you communicate more effectively together.

Your survey report can contain an automated table of contents, embedded Excel sheets of tables, interactive Tableau charts, PDF presentations, Google Form surveys, and much more! Having this information in one place allows you to easily add context to each element you share. Reduce the amount of scattered data and information and tie it together beautifully in one place.

When you’re ready to share it with your world, you can invite your team members to view your report inside of Bit. You can also share it with a live link, embed it on a website, or share a trackable link to track the engagement levels of your report. If there need to be additional security layers placed, you can invite your audience in as guests where they need to login to view your survey report.

Bit will change the way you communicate and is the ultimate tool necessary to create impressive survey reports!

Our team at  bit.ai  has created a few awesome business templates to make your business processes more efficient. Make sure to check them out before you go, y our team might need them!

• SWOT Analysis Template
• Business Proposal Template
• Business Plan Template
• Competitor Research Template
• Project Proposal Template
• Company Fact Sheet
• Executive Summary Template
• Operational Plan Template
• Pitch Deck Template

Crafting a compelling survey report takes effort, but ensuring its clarity and professionalism is crucial. Before hitting publish, use this checklist to give your report a final polish:

• Clear Introduction: Does your introduction effectively introduce the research question, survey methodology, and target audience?
• Actionable Insights: Does your discussion section translate findings into actionable insights for your audience?
• Objectives: Are the objectives specific, measurable, achievable, relevant, and time-bound (SMART)?
• Author Information: Have you included your name, affiliation (if applicable), and contact information for further inquiries?
• Formatting Consistency: Is your report formatted consistently throughout (headings, font size, margins, etc.)?
• Visually Appealing: Are your data visualizations clear, easy to understand, and professionally designed?
• Grammar and Proofreading: Have you meticulously proofread your report for grammatical errors, typos, and sentence structure issues?
• Citations: Are all sources properly cited using a consistent style guide (APA, MLA, etc.)?

Conducting a survey isn’t easy.

From preparing the questionnaire to interpreting and presenting the data, it can seem like a heck of a job.

With Bit.ai’s smart document collaboration platform, at least you don’t have to worry about creating an interactive, impressive survey report!

So what are you waiting for?

Try out Bit’s survey report template and let us know how you liked it by tweeting @bit_docs.

Que: What are three types of survey reports?

Three common types of survey reports include descriptive reports (summarizing findings), analytical reports (interpreting data), and comparative reports (comparing results across groups or time).

Que: What is the purpose of writing a survey report?

The purpose of writing a survey report is to communicate the findings of a survey clearly and comprehensively. It serves to inform stakeholders, decision-makers, or the public about survey results, their implications, and potential actions.

Que: What are the 8 parts of survey report?

A typical survey report includes:

• Introduction
• Objectives and scope
• Executive summary
• Findings and analysis
• Recommendations
• Appendices (optional, for detailed data)

Que: What is a full survey report?

A full survey report is a comprehensive document that details the entire process and outcomes of a survey. It typically includes information on objectives, methodology, findings, analysis, conclusions, and recommendations.

Que: What are the 5 survey methods?

Common survey methods include:

• Questionnaires (online, paper-based)
• Interviews (structured, semi-structured, unstructured)
• Focus groups
• Observation
• Experiments (controlled studies)

Further reads:

How To Create An Effective Status Report?

7 Types of Reports Your Business Certainly Needs!

Incident Report: What is it & How to Write it the Right Way!

Performance Report: What is it & How to Create it? (Steps Included)

Business Report: What is it & How to Write it? (Steps & Format)

Marketing Report: Definition, Types, Benefits & Things to Include!

Sales Report: What is it and How to Create One?

How to Embed Airtable Database in your Bit Documents?

Quality Management Plan: What is it and How to Create it?

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About Bit.ai

Bit.ai is the essential next-gen workplace and document collaboration platform. that helps teams share knowledge by connecting any type of digital content. With this intuitive, cloud-based solution, anyone can work visually and collaborate in real-time while creating internal notes, team projects, knowledge bases, client-facing content, and more.

The smartest online Google Docs and Word alternative, Bit.ai is used in over 100 countries by professionals everywhere, from IT teams creating internal documentation and knowledge bases, to sales and marketing teams sharing client materials and client portals.

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Survey data analysis and best practices for reporting.

20 min read Data can do beautiful things, but turning your survey results into clear, compelling analysis isn’t always a straightforward task. We’ve collected our tips for survey analysis along with a beginner’s guide to survey data and analysis tools.

What is survey data analysis?

Survey analysis is the process of turning the raw material of your survey data into insights and answers you can use to improve things for your business. It’s an essential part of doing survey-based research .

There are a huge number of survey data analysis methods available, from simple cross-tabulation , where data from your survey responses is arranged into rows and columns that make it easier to understand, to statistical methods for survey data analysis which tell you things you could never work out on your own, such as whether the results you’re seeing have statistical significance.

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Types of survey data

Different kinds of survey questions yield data in different forms. Here’s a quick guide to a few of them. Often, survey data will belong to more than one of these categories as they frequently overlap.

Quantitative data vs. qualitative data

What’s the difference between qualitative data and quantitative data?

• Quantitative data, aka numerical data, involves numerical values and quantities. An example of quantitative data would be the number of times a customer has visited a location, the temperature of a city or the scores achieved in an NPS survey .
• Qualitative data is information that isn’t numerical. It may be verbal or visual, or consist of spoken audio or video. It’s more likely to be descriptive or subjective, although it doesn’t have to be. Qualitative data highlights the “why” behind the what.

Closed-ended questions

These are questions with a limited range of responses. They could be a ‘yes’ or ‘no’ question such as ‘do you live in Portland, OR?’. Closed-ended questions can also take the form of multiple-choice, ranking, or drop-down menu items. Respondents can’t qualify their choice between the options or explain why they chose which one they did.

This type of question produces structured data that is easy to sort, code and quantify since the responses will fit into a limited number of ‘buckets’. However, its simplicity means you lose out on some of the finer details that respondents could have provided.

Natural language data (open-ended questions)

Answers written in the respondent’s own words are also a form of survey data. This type of response is usually given in open field (text box) question formats. Questions might begin with ‘how,’ ‘why,’ ‘describe…’ or other conversational phrases that encourage the respondent to open up.

This type of data, known as unstructured data , is rich in information. It typically requires advanced tools such as Natural Language Processing and sentiment analysis to extract the full value from how the respondents answered, because of its complexity and volume.

Categorical (nominal) data

This kind of data exists in categories that have no hierarchical relationship to each other. No item is treated as being more or less, better or worse, than the others. Examples would be primary colors (red v. blue), genders (male v female) or brand names (Chrysler v Mitsubishi).

Multiple choice questions often produce this kind of data (though not always).

Ordinal data

Unlike categorical data, ordinal data has an intrinsic rank that relates to quantity or quality, such as degrees of preference, or how strongly someone agrees or disagrees with a statement.

Likert scales and ranking scales often serve up this kind of data.

Scalar data

Like ordinal data, scalar data deals with quantity and quality on a relative basis, with some items ranking above others. What makes it different is that it uses an established scale, such as age (expressed as a number), test scores (out of 100), or time (in days, hours, minutes etc.)

You might get this kind of data from a drop-down or sliding scale question format, among others.

The type of data you receive affects the kind of survey results analysis you’ll be doing, so it’s very important to consider the type of survey data you will end up with when you’re writing your survey questions and designing survey flows .

Steps to analyze your survey data

Here’s an overview of how you can analyze survey data, identify trends and hopefully draw meaningful conclusions from your research.

1.   Review your research questions

Research questions are the underlying questions your survey seeks to answer. Research questions are not the same as the questions in your questionnaire , although they may cover similar ground.

It’s important to review your research questions before you analyze your survey data to determine if it aligns with what you want to accomplish and find out from your data.

2.   Cross-tabulate your data

Cross-tabulation is a valuable step in sifting through your data and uncovering its meaning. When you cross-tabulate, you’re breaking out your data according to the sub-groups within your research population or your sample, and comparing the relationship between one variable and another. The table you produce will give you an overall picture of how responses vary among your subgroups.

Target the survey questions that best address your research question. For example, if you want to know how many people would be interested in buying from you in the future, cross-tabulating the data will help you see whether some groups were more likely than others to want to return. This gives you an idea of where to focus your efforts when improving your product design or your customer experience .

Cross-tabulation works best for categorical data and other types of structured data. You can cross-tabulate your data in multiple ways across different questions and sub-groups using survey analysis software . Be aware, though, that slicing and dicing your data very finely will give you a smaller sample size, which then affects the reliability of your results.

1.   Review and investigate your results

Put your results in context – how have things changed since the last time you researched these kinds of questions? Do your findings tie in to changes in your market or other research done within your company?

Look at how different demographics within your sample or research population have answered, and compare your findings to other data on these groups. For example, does your survey analysis tell you something about why a certain group is purchasing less, or more? Does the data tell you anything about how well your company is meeting strategic goals, such as changing brand perceptions or appealing to a younger market?

Look at quantitative measures too. Which questions were answered the most? Which ones produced the most polarized responses? Were there any questions with very skewed data? This could be a clue to issues with survey design .

2.   Use statistical analysis to check your findings

Statistics give you certainty (or as close to it as you can get) about the results of your survey. Statistical tools like T-test, regression and ANOVA help you make sure that the results you’re seeing have statistical significance and aren’t just there by chance.

Statistical tools can also help you determine which aspects of your data are most important, and what kinds of relationships – if any – they have with one another.

Benchmarking your survey data

One of the most powerful aspects of survey data analysis is its ability to build on itself. By repeating market research surveys at different points in time, you can not only use it to uncover insights from your results, but to strengthen those insights over time.

Using consistent types of data and methods of analysis means you can use your initial results as a benchmark for future research . What’s changed year-on-year? Has your survey data followed a steady rise, performed a sudden leap or fallen incrementally? Over time, all these questions become answerable when you listen regularly and analyze your data consistently.

Maintaining your question and data types and your data analysis methods means you achieve a like-for-like measurement of results over time. And if you collect data consistently enough to see patterns and processes emerging, you can use these to make predictions about future events and outcomes.

Another benefit of data analysis over time is that you can compare your results with other people’s, provided you are using the same measurements and metrics. A classic example is NPS (Net Promoter Score) , which has become a standard measurement of customer experience that companies typically track over time.

How to present survey results

Most data isn’t very friendly to the human eye or brain in its raw form. Survey data analysis helps you turn your data into something that’s accessible, intuitive, and even interesting to a wide range of people.

1.   Make it visual

You can present data in a visual form, such as a chart or graph, or put it into a tabular form so it’s easy for people to see the relationships between variables in your crosstab analysis. Choose a graphic format that best suits your data type and clearly shows the results to the untrained eye. There are plenty of options, including linear graphs, bar graphs, Venn diagrams, word clouds and pie charts. If time and budget allows, you can create an infographic or animation.

2.   Keep language human

You can express discoveries in plain language, for example, in phrases like “customers in the USA consistently preferred potato chips to corn chips.” Adding direct quotes from your natural language data (provided respondents have consented to this) can add immediacy and illustrate your points.

3.   Tell the story of your research

Another approach is to express data using the power of storytelling, using a beginning-middle-end or situation-crisis-resolution structure to talk about how trends have emerged or challenges have been overcome. This helps people understand the context of your research and why you did it the way you did.

4.   Include your insights

As well as presenting your data in terms of numbers and proportions, always be sure to share the insights it has produced too. Insights come when you apply knowledge and ideas to the data in the survey, which means they’re often more striking and easier to grasp than the data by itself. Insights may take the form of a recommended action , or examine how two different data points are connected.

Common mistakes in analyzing data and how to avoid them

1.   being too quick to interpret survey results.

It’s easy to get carried away when the data seems to show the results you were expecting or confirms a hypothesis you started with. This is why it’s so important to use statistics to make sure your survey report is statistically significant, i.e. based on reality, not a coincidence. Remember that a skewed or coincidental result becomes more likely with a smaller sample size.

2.   Treating correlation like causation

You may have heard the phrase “correlation is not causation” before. It’s well-known for a reason: mistaking a link between two independent variables as a causal relationship between them is a common pitfall in research. Results can correlate without one having a direct effect on the other.

An example is when there is another common variable involved that isn’t measured and acts as a kind of missing link between the correlated variables. Sales of sunscreen might go up in line with the number of ice-creams sold at the beach, but it’s not because there’s something about ice-cream that makes people more vulnerable to getting sunburned. It’s because a third variable – sunshine – affects both sunscreen use and ice-cream sales.

3.   Missing the nuances in qualitative natural language data

Human language is complex, and analyzing survey data in the form of speech or text isn’t as straightforward as mapping vocabulary items to positive or negative codes. The latest AI solutions go further, uncovering meaning, emotion and intent within human language.

Trusting your rich qualitative data to an AI’s interpretation means relying on the software’s ability to understand language in the way a human would, taking into account things like context and conversational dynamics. If you’re investing in software to analyze natural language data in your surveys, make sure it’s capable of sentiment analysis that uses machine learning to get a deeper understanding of what survey respondents are trying to tell you.

Tools for survey analysis

If you’re planning to run an ongoing data insights program (and we recommend that you do), it’s important to have tools on hand that make it easy and efficient to perform your research and extract valuable insights from the results.

It’s even better if those tools help you to share your findings with the right people, at the right time, in a format that works for them. Here are a few attributes to look for in a survey analysis software platform.

• Easy to use (for non-experts) Look for software that demands minimal training or expertise, and you’ll save time and effort while maximizing the number of people who can pitch in on your experience management program . User-friendly drag-and-drop interfaces, straightforward menus, and automated data analysis are all worth looking out for.
• Works on any platform Don’t restrict your team to a single place where software is located on a few terminals. Instead, choose a cloud-based platform that’s optimized for mobile, desktop, tablet and more.
• Integrates with your existing setup Stand-alone analysis tools create additional work you shouldn’t have to do. Why export, convert, paste and print out when you can use a software tool that plugs straight into your existing systems via API?
• Incorporates statistical analysis Choose a system that gives you the tools to not just process and present your data, but refine your survey results using statistical tools that generate deep insights and future predictions with just a few clicks.
• Comes with first-class support The best survey data tool is one that scales with you and adapts to your goals and growth. A large part of that is having an expert team on call to answer questions, propose bespoke solutions, and help you get the most out of the service you’ve paid for.

Tips from the team at Qualtrics

We’ve run more than a few survey research programs in our time, and we have some tips to share that you may not find in the average survey data analysis guide. Here are some innovative ways to help make sure your survey analysis hits the mark, grabs attention, and provokes change.

Write the headlines

The #1 way to make your research hit the mark is to start with the end in mind. Before you even write your survey questions, make sample headlines of what the survey will discover. Sample headlines are the main data takeaways from your research. Some sample headlines might be:

• The #1 concern that travelers have with staying at our hotel is X
• X% of visitors to our showroom want to be approached by a salesperson within the first 10 minutes
• Diners are X% more likely to choose our new lunch menu than our old one

You may even want to sketch out mock charts that show how the data will look in your results. If you “write” the results first, those results become a guide to help you design questions that ensure you get the data you want.

Gut Data Gut

We live in a data-driven society. Marketing is a data-driven business function. But don’t be afraid to overlap qualitative research findings onto your quantitative data . Don’t be hesitant to apply what you know in your gut with what you know from the data.

This is called “Gut Data Gut”. Check your gut, check your data, and check your gut. If you have personal experience with the research topic, use it! If you have qualitative research that supports the data, use it!

Your survey is one star in a constellation of information that combines to tell a story. Use every atom of information at your disposal. Just be sure to let your audience know when you are showing them findings from statistically significant research and when it comes from a different source.

Write a mock press release to encourage taking action

One of the biggest challenges of research is acting on it . This is sometimes called the “Knowing / Doing Gap” where an organization has a difficult time implementing truths they know.

One way you can ignite change with your research is to write a press release dated six months into the future that proudly announces all the changes as a result of your research. Maybe it touts the three new features that were added to your product. Perhaps it introduces your new approach to technical support. Maybe it outlines the improvements to your website.

After six months, gather your team and read the press release together to see how well you executed change based on the research.

Focus your research findings

Everyone consumes information differently. Some people want to fly over your findings at 30,000 feet and others want to slog through the weeds in their rubber boots. You should package your research for these different research consumer types.

Package your survey results analysis findings in 5 ways:

• A 1-page executive summary with key insights
• A 1-page stat sheet that ticks off the top supporting stats
• A shareable slide deck with data visuals that can be understood as a stand-alone or by being presented in person
• Live dashboards with all the survey data that allow team members to filter the data and dig in as deeply as they want on a DIY basis
• The Mock Press Release (mentioned above)

How to analyze survey data

Reporting on survey results will prove the value of your work. Learn more about statistical analysis types or jump into an analysis type below to see our favorite tools of the trade:

• Conjoint Analysis
• CrossTab Analysis
• Cluster Analysis
• Factor Analysis
• Analysis of Variance (ANOVA)

eBook: 3 steps to turn CX insights into business impact

Related resources

Analysis & Reporting

Margin of error 11 min read

Data saturation in qualitative research 8 min read, thematic analysis 11 min read, behavioral analytics 12 min read, statistical significance calculator: tool & complete guide 18 min read, regression analysis 19 min read, data analysis 31 min read, request demo.

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• v.35(45); 2020 Nov 23

Reporting Survey Based Studies – a Primer for Authors

Prithvi sanjeevkumar gaur.

1 Smt. Kashibai Navale Medical College and General Hospital, Pune, India.

Olena Zimba

2 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Vikas Agarwal

3 Department Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Latika Gupta

Associated data.

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.

Graphical Abstract

INTRODUCTION

Surveys are the principal method used to address topics that require individual self-report about beliefs, knowledge, attitudes, opinions or satisfaction, which cannot be assessed using other approaches. 1 This research method allows information to be collected by asking a set of questions on a specific topic to a subset of people and generalizing the results to a larger population. Assessment of opinions in a valid and reliable way require clear, structured and precise reporting of results. This is possible with a survey based out of a meticulous design, followed by validation and pilot testing. 2 The aim of this opinion piece is to provide practical advice to conduct survey-based research. It details the ethical and methodological aspects to be undertaken while performing a survey, the online platforms available for distributing survey, and the implications of survey-based research.

Survey-based research is a means to obtain quick data, and such studies are relatively easy to conduct and analyse, and are cost-effective (under a majority of the circumstances). 3 These are also one of the most convenient methods of obtaining data about rare diseases. 4 With major technological advancements and improved global interconnectivity, especially during the coronavirus disease 2019 (COVID-19) pandemic, surveys have surpassed other means of research due to their distinctive advantage of a wider reach, including respondents from various parts of the world having diverse cultures and geographically disparate locations. Moreover, survey-based research allows flexibility to the investigator and respondent alike. 5 While the investigator(s) may tailor the survey dates and duration as per their availability, the respondents are allowed the convenience of responding to the survey at ease, in the comfort of their homes, and at a time when they can answer the questions with greater focus and to the best of their abilities. 6 Respondent biases inherent to environmental stressors can be significantly reduced by this approach. 5 It also allows responses across time-zones, which may be a major impediment to other forms of research or data-collection. This allows distant placement of the investigator from the respondents.

Various digital tools are now available for designing surveys ( Table 1 ). 7 Most of these are free with separate premium paid options. The analysis of data can be made simpler and cleaning process almost obsolete by minimising open-ended answer choices. 8 Close-ended answers makes data collection and analysis efficient, by generating an excel which can be directly accessed and analysed. 9 Minimizing the number of questions and making all questions mandatory can further aid this process by bringing uniformity to the responses and analysis simpler. Surveys are arguably also the most engaging form of research, conditional to the skill of the investigator.

Q/t = questions per typeform, A/m = answers per month, Q/s = questions per survey, A/s = answers per survey, NA = not applicable, NPS = net promoter score.

Data protection laws now mandate anonymity while collecting data for most surveys, particularly when they are exempt from ethical review. 10 , 11 Anonymization has the potential to reduce (or at times even eliminate) social desirability bias which gains particular relevance when targeting responses from socially isolated or vulnerable communities (e.g. LGBTQ and low socio-economic strata communities) or minority groups (religious, ethnic and medical) or controversial topics (drug abuse, using language editing software).

Moreover, surveys could be the primary methodology to explore a hypothesis until it evolves into a more sophisticated and partly validated idea after which it can be probed further in a systematic and structured manner using other research methods.

The aim of this paper is to reduce the incorrect reporting of surveys. The paper also intends to inform researchers of the various aspects of survey-based studies and the multiple points that need to be taken under consideration while conducting survey-based research.

SURVEYS IN THE COVID-19 PANDEMIC

The COVID-19 has led to a distinctive rise in survey-based research. 12 The need to socially distance amid widespread lockdowns reduced patient visits to the hospital and brought most other forms of research to a standstill in the early pandemic period. A large number of level-3 bio-safety laboratories are being engaged for research pertaining to COVID-19, thereby limiting the options to conduct laboratory-based research. 13 , 14 Therefore, surveys appear to be the most viable option for researchers to explore hypotheses related to the situation and its impact in such times. 15

LIMITATIONS WHILE CONDUCTING SURVEY-BASED RESEARCH

Designing a fine survey is an arduous task and requires skill even though clear guidelines are available in regard to the same. Survey design requires extensive thoughtfulness on the core questions (based on the hypothesis or the primary research question), with consideration of all possible answers, and the inclusion of open-ended options to allow recording other possibilities. A survey should be robust, in regard to the questions gathered and the answer choices available, it must be validated, and pilot tested. 16 The survey design may be supplanted with answer choices tailored for the convenience of the responder, to reduce the effort while making it more engaging. Survey dissemination and engagement of respondents also requires experience and skill. 17

Furthermore, the absence of an interviewer prevents us from gaining clarification on responses of open-ended questions if any. Internet surveys are also prone to survey fraud by erroneous reporting. Hence, anonymity of surveys is a boon and a bane. The sample sizes are skewed as it lacks representation of population absent on the Internet like the senile or the underprivileged. The illiterate population also lacks representation in survey-based research.

The “Enhancing the QUAlity and Transparency Of health Research” network (EQUATOR) provides two separate guidelines replete with checklists to ensure valid reporting of e-survey methodology. These include “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist.

COMMON TYPES OF SURVEY-BASED RESEARCH

From a clinician's standpoint, the common survey types include those centered around problems faced by the patients or physicians. 18 Surveys collecting the opinions of various clinicians on a debated clinical topic or feedback forms typically served after attending medical conferences or prescribing a new drug or trying a new method for a given procedure are also surveys. The formulation of clinical practice guidelines entails Delphi exercises using paper surveys, which are yet another form of survey-mediated research.

Size of the survey depends on its intent. They could be large or small surveys. Therefore, identification of the intent behind the survey is essential to allow the investigator to form a hypothesis and then explore it further. Large population-based or provider-based surveys are often done and generate mammoth data over the years. E.g. The National Health and Nutrition Examination Survey, The National Health Interview Survey and the National Ambulatory Medical Care Survey.

SCENARIOS FOR CONDUCTING SURVEY-BASED RESEARCH

Despite all said and done about the convenience of conducting survey-based research, it is prudent to conduct a feasibility check before embarking on one. Certain scenarios may be the key determinants in determining the fate of survey-based research ( Table 2 ).

ETHICS APPROVAL FOR SURVEY-BASED RESEARCH

Approval from the Institutional Review Board should be taken as per requirement according to the CHERRIES checklist. However, rules for approval are different as per the country or nation and therefore, local rules must be checked and followed. For instance, in India, the Indian Council of Medical Research released an article in 2017, stating that the concept of broad consent has been updated which is defined “consent for an unspecified range of future research subject to a few contents and/or process restrictions.” It talks about “the flexibility of Indian ethics committees to review a multicentric study proposal for research involving low or minimal risk, survey or studies using anonymized samples or data or low or minimal risk public health research.” The reporting of approvals received and applied for and the procedure of written, informed consent followed must be clear and transparent. 10 , 19

The use of incentives in surveys is also an ethical concern. 20 The different of incentives that can be used are monetary or non-monetary. Monetary incentives are usually discouraged as these may attract the wrong population due to the temptation of the monetary benefit. However, monetary incentives have been seen to make survey receive greater traction even though this is yet to proven. Monetary incentives are not only provided in terms of cash or cheque but also in the form of free articles, discount coupons, phone cards, e-money or cashback value. 21 These methods though tempting must be seldom used. If used, their use must be disclosed and justified in the report. The use of non-monetary incentives like a meeting with a famous personality or access to restricted and authorized areas. These can also help pique the interest of the respondents.

DESIGNING A SURVEY

As mentioned earlier, the design of a survey is reflective of the skill of the investigator curating it. 22 Survey builders can be used to design an efficient survey. These offer majority of the basic features needed to construct a survey, free of charge. Therefore, surveys can be designed from scratch, using pre-designed templates or by using previous survey designs as inspiration. Taking surveys could be made convenient by using the various aids available ( Table 1 ). Moreover, even the investigator should be mindful of the unintended response effects of ordering and context of survey questions. 23

Surveys using clear, unambiguous, simple and well-articulated language record precise answers. 24 A well-designed survey accounts for the culture, language and convenience of the target demographic. The age, region, country and occupation of the target population is also considered before constructing a survey. Consistency is maintained in the terms used in the survey and abbreviations are avoided to allow the respondents to have a clear understanding of the question being answered. Universal abbreviations or previously indexed abbreviations maintain the unambiguity of the survey.

Surveys beginning with broad, easy and non-specific questions as compared to sensitive, tedious and non-specific ones receive more accurate and complete answers. 25 Questionnaires designed such that the relatively tedious and long questions requiring the respondent to do some nit-picking are placed at the end improves the response rate of the survey. This prevents the respondent to be discouraged to answer the survey at the beginning itself and motivates the respondent to finish the survey at the end. All questions must provide a non-response option and all questions should be made mandatory to increase completeness of the survey. Questions can be framed in close-ended or open-ended fashion. However, close-ended questions are easier to analyze and are less tedious to answer by the respondent and therefore must be the main component in a survey. Open-ended questions have minimal use as they are tedious, take time to answer and require fine articulation of one's thoughts. Also, their minimal use is advocated because the interpretation of such answers requires dedication in terms of time and energy due to the diverse nature of the responses which is difficult to promise owing to the large sample sizes. 26 However, whenever the closed choices do not cover all probabilities, an open answer choice must be added. 27 , 28

Screening questions to meet certain criteria to gain access to the survey in cases where inclusion criteria need to be established to maintain authenticity of target demographic. Similarly, logic function can be used to apply an exclusion. This allows clean and clear record of responses and makes the job of an investigator easier. The respondents can or cannot have the option to return to the previous page or question to alter their answer as per the investigator's preference.

The range of responses received can be reduced in case of questions directed towards the feelings or opinions of people by using slider scales, or a Likert scale. 29 , 30 In questions having multiple answers, check boxes are efficient. When a large number of answers are possible, dropdown menus reduce the arduousness. 31 Matrix scales can be used to answer questions requiring grading or having a similar range of answers for multiple conditions. Maximum respondent participation and complete survey responses can be ensured by reducing the survey time. Quiz mode or weighted modes allow the respondent to shuffle between questions and allows scoring of quizzes and can be used to complement other weighted scoring systems. 32 A flowchart depicting a survey construct is presented as Fig. 1 .

Survey validation

Validation testing though tedious and meticulous, is worthy effort as the accuracy of a survey is determined by its validity. It is indicative of the of the sample of the survey and the specificity of the questions such that the data acquired is streamlined to answer the questions being posed or to determine a hypothesis. 33 , 34 Face validation determines the mannerism of construction of questions such that necessary data is collected. Content validation determines the relation of the topic being addressed and its related areas with the questions being asked. Internal validation makes sure that the questions being posed are directed towards the outcome of the survey. Finally, Test – retest validation determines the stability of questions over a period of time by testing the questionnaire twice and maintaining a time interval between the two tests. For surveys determining knowledge of respondents pertaining to a certain subject, it is advised to have a panel of experts for undertaking the validation process. 2 , 35

Reliability testing

If the questions in the survey are posed in a manner so as to elicit the same or similar response from the respondents irrespective of the language or construction of the question, the survey is said to be reliable. It is thereby, a marker of the consistency of the survey. This stands to be of considerable importance in knowledge-based researches where recall ability is tested by making the survey available for answering by the same participants at regular intervals. It can also be used to maintain authenticity of the survey, by varying the construction of the questions.

Designing a cover letter

A cover letter is the primary means of communication with the respondent, with the intent to introduce the respondent to the survey. A cover letter should include the purpose of the survey, details of those who are conducting it, including contact details in case clarifications are desired. It should also clearly depict the action required by the respondent. Data anonymization may be crucial to many respondents and is their right. This should be respected in a clear description of the data handling process while disseminating the survey. A good cover letter is the key to building trust with the respondent population and can be the forerunner to better response rates. Imparting a sense of purpose is vital to ideationally incentivize the respondent population. 36 , 37 Adding the credentials of the team conducting the survey may further aid the process. It is seen that an advance intimation of the survey prepares the respondents while improving their compliance.

The design of a cover letter needs much attention. It should be captivating, clear, precise and use a vocabulary and language specific to the target population for the survey. Active voice should be used to make a greater impact. Crowding of the details must be avoided. Using italics, bold fonts or underlining may be used to highlight critical information. the tone ought to be polite, respectful, and grateful in advance. The use of capital letters is at best avoided, as it is surrogate for shouting in verbal speech and may impart a bad taste.

The dates of the survey may be intimated, so the respondents may prepare themselves for taking it at a time conducive to them. While, emailing a closed group in a convenience sampled survey, using the name of the addressee may impart a customized experience and enhance trust building and possibly compliance. Appropriate use of salutations like Mr./Ms./Mrs. may be considered. Various portals such as SurveyMonkey allow the researchers to save an address list on the website. These may then be reached out using an embedded survey link from a verified email address to minimize bouncing back of emails.

The body of the cover letter must be short, crisp and not exceed 2–3 paragraphs under idea circumstances. Ernest efforts to protect confidentiality may go a long way in enhancing response rates. 38 While it is enticing to provide incentives to enhance response, these are best avoided. 38 , 39 In cases when indirect incentives are offered, such as provision of results of the survey, these may be clearly stated in the cover letter. Lastly, a formal closing note with the signatures of the lead investigator are welcome. 38 , 40

Designing questions

Well-constructed questionnaires are essentially the backbone of successful survey-based studies. With this type of research, the primary concern is the adequate promotion and dissemination of the questionnaire to the target population. The careful of selection of sample population, therefore, needs to be with minimal flaws. The method of conducting survey is an essential determinant of the response rate observed. 41 Broadly, surveys are of two types: closed and open. Depending on the sample population the method of conducting the survey must be determined.

Various doctors use their own patients as the target demographic, as it improves compliance. However, this is effective in surveys aiming towards a geographically specific, fairly common disease as the sample size needs to be adequate. Response bias can be identified by the data collected from respondent and non-respondent groups. 42 , 43 Therefore, to choose a target population whose database of baseline characteristics is already known is more efficacious. In cases of surveys focused on patients having a rare group of diseases, online surveys or e-surveys can be conducted. Data can also be gathered from the multiple national organizations and societies all over the world. 44 , 45 Computer generated random selection can be done from this data to choose participants and they can be reached out to using emails or social media platforms like WhatsApp and LinkedIn. In both these scenarios, closed questionnaires can be conducted. These have restricted access either through a URL link or through e-mail.

In surveys targeting an issue faced by a larger demographic (e.g. pandemics like the COVID-19, flu vaccines and socio-political scenarios), open surveys seem like the more viable option as they can be easily accessed by majority of the public and ensures large number of responses, thereby increasing the accuracy of the study. Survey length should be optimal to avoid poor response rates. 25 , 46

SURVEY DISSEMINATION

Uniform distribution of the survey ensures equitable opportunity to the entire target population to access the questionnaire and participate in it. While deciding the target demographic communities should be studied and the process of “lurking” is sometimes practiced. Multiple sampling methods are available ( Fig. 1 ). 47

Distribution of survey to the target demographic could be done using emails. Even though e-mails reach a large proportion of the target population, an unknown sender could be blocked, making the use of personal or a previously used email preferable for correspondence. Adding a cover letter along with the invite adds a personal touch and is hence, advisable. Some platforms allow the sender to link the survey portal with the sender's email after verifying it. Noteworthily, despite repeated email reminders, personal communication over the phone or instant messaging improved responses in the authors' experience. 48 , 49

Distribution of the survey over other social media platforms (SMPs, namely WhatsApp, Facebook, Instagram, Twitter, LinkedIn etc.) is also practiced. 50 , 51 , 52 Surveys distributed on every available platform ensures maximal outreach. 53 Other smartphone apps can also be used for wider survey dissemination. 50 , 54 It is important to be mindful of the target population while choosing the platform for dissemination of the survey as some SMPs such as WhatsApp are more popular in India, while others like WeChat are used more widely in China, and similarly Facebook among the European population. Professional accounts or popular social accounts can be used to promote and increase the outreach for a survey. 55 Incentives such as internet giveaways or meet and greets with their favorite social media influencer have been used to motivate people to participate.

However, social-media platforms do not allow calculation of the denominator of the target population, resulting in inability to gather the accurate response rate. Moreover, this method of collecting data may result in a respondent bias inherent to a community that has a greater online presence. 43 The inability to gather the demographics of the non-respondents (in a bid to identify and prove that they were no different from respondents) can be another challenge in convenience sampling, unlike in cohort-based studies.

Lastly, manually filling of surveys, over the telephone, by narrating the questions and answer choices to the respondents is used as the last-ditch resort to achieve a high desired response rate. 56 Studies reveal that surveys released on Mondays, Fridays, and Sundays receive more traction. Also, reminders set at regular intervals of time help receive more responses. Data collection can be improved in collaborative research by syncing surveys to fill out electronic case record forms. 57 , 58 , 59

Data anonymity refers to the protection of data received as a part of the survey. This data must be stored and handled in accordance with the patient privacy rights/privacy protection laws in reference to surveys. Ethically, the data must be received on a single source file handled by one individual. Sharing or publishing this data on any public platform is considered a breach of the patient's privacy. 11 In convenience sampled surveys conducted by e-mailing a predesignated group, the emails shall remain confidential, as inadvertent sharing of these as supplementary data in the manuscript may amount to a violation of the ethical standards. 60 A completely anonymized e-survey discourages collection of Internet protocol addresses in addition to other patient details such as names and emails.

Data anonymity gives the respondent the confidence to be candid and answer the survey without inhibitions. This is especially apparent in minority groups or communities facing societal bias (sex workers, transgenders, lower caste communities, women). Data anonymity aids in giving the respondents/participants respite regarding their privacy. As the respondents play a primary role in data collection, data anonymity plays a vital role in survey-based research.

DATA HANDLING OF SURVEYS

The data collected from the survey responses are compiled in a .xls, .csv or .xlxs format by the survey tool itself. The data can be viewed during the survey duration or after its completion. To ensure data anonymity, minimal number of people should have access to these results. The data should then be sifted through to invalidate false, incorrect or incomplete data. The relevant and complete data should then be analyzed qualitatively and quantitatively, as per the aim of the study. Statistical aids like pie charts, graphs and data tables can be used to report relative data.

ANALYSIS OF SURVEY DATA

Analysis of the responses recorded is done after the time made available to answer the survey is complete. This ensures that statistical and hypothetical conclusions are established after careful study of the entire database. Incomplete and complete answers can be used to make analysis conditional on the study. Survey-based studies require careful consideration of various aspects of the survey such as the time required to complete the survey. 61 Cut-off points in the time frame allow authentic answers to be recorded and analyzed as compared to disingenuous completed questionnaires. Methods of handling incomplete questionnaires and atypical timestamps must be pre-decided to maintain consistency. Since, surveys are the only way to reach people especially during the COVID-19 pandemic, disingenuous survey practices must not be followed as these will later be used to form a preliminary hypothesis.

REPORTING SURVEY-BASED RESEARCH

Reporting the survey-based research is by far the most challenging part of this method. A well-reported survey-based study is a comprehensive report covering all the aspects of conducting a survey-based research.

The design of the survey mentioning the target demographic, sample size, language, type, methodology of the survey and the inclusion-exclusion criteria followed comprises a descriptive report of a survey-based study. Details regarding the conduction of pilot-testing, validation testing, reliability testing and user-interface testing add value to the report and supports the data and analysis. Measures taken to prevent bias and ensure consistency and precision are key inclusions in a report. The report usually mentions approvals received, if any, along with the written, informed, consent taken from the participants to use the data received for research purposes. It also gives detailed accounts of the different distribution and promotional methods followed.

A detailed account of the data input and collection methods along with tools used to maintain the anonymity of the participants and the steps taken to ensure singular participation from individual respondents indicate a well-structured report. Descriptive information of the website used, visitors received and the externally influencing factors of the survey is included. Detailed reporting of the post-survey analysis including the number of analysts involved, data cleaning required, if any, statistical analysis done and the probable hypothesis concluded is a key feature of a well-reported survey-based research. Methods used to do statistical corrections, if used, should be included in the report. The EQUATOR network has two checklists, “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist, that can be utilized to construct a well-framed report. 62 , 63 Importantly, self-reporting of biases and errors avoids the carrying forward of false hypothesis as a basis of more advanced research. References should be cited using standard recommendations, and guided by the journal specifications. 64

CHOOSING A TARGET JOURNAL FOR SURVEY-BASED RESEARCH

Surveys can be published as original articles, brief reports or as a letter to the editor. Interestingly, most modern journals do not actively make mention of surveys in the instructions to the author. Thus, depending on the study design, the authors may choose the article category, cohort or case-control interview or survey-based study. It is prudent to mention the type of study in the title. Titles albeit not too long, should not exceed 10–12 words, and may feature the type of study design for clarity after a semicolon for greater citation potential.

While the choice of journal is largely based on the study subject and left to the authors discretion, it may be worthwhile exploring trends in a journal archive before proceeding with submission. 65 Although the article format is similar across most journals, specific rules relevant to the target journal may be followed for drafting the article structure before submission.

RETRACTION OF ARTICLES

Articles that are removed from the publication after being released are retracted articles. These are usually retracted when new discrepancies come to light regarding, the methodology followed, plagiarism, incorrect statistical analysis, inappropriate authorship, fake peer review, fake reporting and such. 66 A sufficient increase in such papers has been noticed. 67

We carried out a search of “surveys” on Retraction Watch on 31st August 2020 and received 81 search results published between November 2006 to June 2020, out of which 3 were repeated. Out of the 78 results, 37 (47.4%) articles were surveys, 23 (29.4%) showed as unknown types and 18 (23.2%) reported other types of research. ( Supplementary Table 1 ). Fig. 2 gives a detailed description of the causes of retraction of the surveys we found and its geographic distribution.

A good survey ought to be designed with a clear objective, the design being precise and focused with close-ended questions and all probabilities included. Use of rating scales, multiple choice questions and checkboxes and maintaining a logical question sequence engages the respondent while simplifying data entry and analysis for the investigator. Conducting pilot-testing is vital to identify and rectify deficiencies in the survey design and answer choices. The target demographic should be defined well, and invitations sent accordingly, with periodic reminders as appropriate. While reporting the survey, maintaining transparency in the methods employed and clearly stating the shortcomings and biases to prevent advocating an invalid hypothesis.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Visualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
• Writing - original draft: Gaur PS, Gupta L.

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Reporting survey based research

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Research Reports: Definition and How to Write Them

Reports are usually spread across a vast horizon of topics but are focused on communicating information about a particular topic and a niche target market. The primary motive of research reports is to convey integral details about a study for marketers to consider while designing new strategies.

Certain events, facts, and other information based on incidents need to be relayed to the people in charge, and creating research reports is the most effective communication tool. Ideal research reports are extremely accurate in the offered information with a clear objective and conclusion. These reports should have a clean and structured format to relay information effectively.

What are Research Reports?

Research reports are recorded data prepared by researchers or statisticians after analyzing the information gathered by conducting organized research, typically in the form of surveys or qualitative methods .

A research report is a reliable source to recount details about a conducted research. It is most often considered to be a true testimony of all the work done to garner specificities of research.

The various sections of a research report are:

• Background/Introduction
• Implemented Methods
• Results based on Analysis
• Deliberation

Learn more: Quantitative Research

Components of Research Reports

Research is imperative for launching a new product/service or a new feature. The markets today are extremely volatile and competitive due to new entrants every day who may or may not provide effective products. An organization needs to make the right decisions at the right time to be relevant in such a market with updated products that suffice customer demands.

The details of a research report may change with the purpose of research but the main components of a report will remain constant. The research approach of the market researcher also influences the style of writing reports. Here are seven main components of a productive research report:

• Research Report Summary: The entire objective along with the overview of research are to be included in a summary which is a couple of paragraphs in length. All the multiple components of the research are explained in brief under the report summary.  It should be interesting enough to capture all the key elements of the report.
• Research Introduction: There always is a primary goal that the researcher is trying to achieve through a report. In the introduction section, he/she can cover answers related to this goal and establish a thesis which will be included to strive and answer it in detail.  This section should answer an integral question: “What is the current situation of the goal?”.  After the research design was conducted, did the organization conclude the goal successfully or they are still a work in progress –  provide such details in the introduction part of the research report.
• Research Methodology: This is the most important section of the report where all the important information lies. The readers can gain data for the topic along with analyzing the quality of provided content and the research can also be approved by other market researchers . Thus, this section needs to be highly informative with each aspect of research discussed in detail.  Information needs to be expressed in chronological order according to its priority and importance. Researchers should include references in case they gained information from existing techniques.
• Research Results: A short description of the results along with calculations conducted to achieve the goal will form this section of results. Usually, the exposition after data analysis is carried out in the discussion part of the report.

Learn more: Quantitative Data

• Research Discussion: The results are discussed in extreme detail in this section along with a comparative analysis of reports that could probably exist in the same domain. Any abnormality uncovered during research will be deliberated in the discussion section.  While writing research reports, the researcher will have to connect the dots on how the results will be applicable in the real world.
• Research References and Conclusion: Conclude all the research findings along with mentioning each and every author, article or any content piece from where references were taken.

Learn more: Qualitative Observation

15 Tips for Writing Research Reports

Writing research reports in the manner can lead to all the efforts going down the drain. Here are 15 tips for writing impactful research reports:

• Prepare the context before starting to write and start from the basics:  This was always taught to us in school – be well-prepared before taking a plunge into new topics. The order of survey questions might not be the ideal or most effective order for writing research reports. The idea is to start with a broader topic and work towards a more specific one and focus on a conclusion or support, which a research should support with the facts.  The most difficult thing to do in reporting, without a doubt is to start. Start with the title, the introduction, then document the first discoveries and continue from that. Once the marketers have the information well documented, they can write a general conclusion.
• Keep the target audience in mind while selecting a format that is clear, logical and obvious to them:  Will the research reports be presented to decision makers or other researchers? What are the general perceptions around that topic? This requires more care and diligence. A researcher will need a significant amount of information to start writing the research report. Be consistent with the wording, the numbering of the annexes and so on. Follow the approved format of the company for the delivery of research reports and demonstrate the integrity of the project with the objectives of the company.
• Have a clear research objective: A researcher should read the entire proposal again, and make sure that the data they provide contributes to the objectives that were raised from the beginning. Remember that speculations are for conversations, not for research reports, if a researcher speculates, they directly question their own research.
• Establish a working model:  Each study must have an internal logic, which will have to be established in the report and in the evidence. The researchers’ worst nightmare is to be required to write research reports and realize that key questions were not included.

Learn more: Quantitative Observation

• Gather all the information about the research topic. Who are the competitors of our customers? Talk to other researchers who have studied the subject of research, know the language of the industry. Misuse of the terms can discourage the readers of research reports from reading further.
• Read aloud while writing. While reading the report, if the researcher hears something inappropriate, for example, if they stumble over the words when reading them, surely the reader will too. If the researcher can’t put an idea in a single sentence, then it is very long and they must change it so that the idea is clear to everyone.
• Check grammar and spelling. Without a doubt, good practices help to understand the report. Use verbs in the present tense. Consider using the present tense, which makes the results sound more immediate. Find new words and other ways of saying things. Have fun with the language whenever possible.
• Discuss only the discoveries that are significant. If some data are not really significant, do not mention them. Remember that not everything is truly important or essential within research reports.

Learn more: Qualitative Data

• Try and stick to the survey questions. For example, do not say that the people surveyed “were worried” about an research issue , when there are different degrees of concern.
• The graphs must be clear enough so that they understand themselves. Do not let graphs lead the reader to make mistakes: give them a title, include the indications, the size of the sample, and the correct wording of the question.
• Be clear with messages. A researcher should always write every section of the report with an accuracy of details and language.
• Be creative with titles – Particularly in segmentation studies choose names “that give life to research”. Such names can survive for a long time after the initial investigation.
• Create an effective conclusion: The conclusion in the research reports is the most difficult to write, but it is an incredible opportunity to excel. Make a precise summary. Sometimes it helps to start the conclusion with something specific, then it describes the most important part of the study, and finally, it provides the implications of the conclusions.
• Get a couple more pair of eyes to read the report. Writers have trouble detecting their own mistakes. But they are responsible for what is presented. Ensure it has been approved by colleagues or friends before sending the find draft out.

Learn more: Market Research and Analysis

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Who is Hispanic?

Debates over who is Hispanic have often fueled conversations about identity among Americans who trace their heritage to Latin America or Spain .

So, who is considered Hispanic in the United States today? How exactly do the federal government and others count the Hispanic population? And what role does race play in deciding who counts as Hispanic?

We’ll answer these and other common questions here.

To answer the question of who is Hispanic, this analysis draws on about five decades of U.S. Census Bureau data and about two decades of Pew Research Center surveys of Hispanic adults in the United States.

National counts of the Latino population come from the Census Bureau’s decennial census (this includes P.L. 94-171 census data ) and official population estimates . The bureau’s American Community Survey (ACS) provides demographic details such as race, country of origin and intermarriage rates. Some ACS data was accessed through IPUMS USA from the University of Minnesota.

Views of Hispanic identity draw on the Center’s National Survey of Latinos (NSL), which is fielded in English and Spanish. The survey has been conducted online since 2019, primarily through the Center’s American Trends Panel (ATP), which is recruited through national, random sampling of residential addresses. This way nearly all adults have a chance of selection. The survey is weighted to be representative of the U.S. Hispanic adult population by gender, Hispanic origin, partisan affiliation, education and other categories. Read more about the ATP’s methodology . The NSL was conducted by phone from 2002 to 2018.

Read further details on how the Census Bureau asked about race and ethnicity and coded responses in the 2020 census. Here is a full list of origin groups that were coded as Hispanic in the 2020 census.

How many Hispanics are in the U.S. today?

The Census Bureau estimates there were 65.2 million Hispanics in the U.S. as of July 1, 2023, a new high. They made up more than 19% of the nation’s population .

How are Hispanics identified and counted in government surveys, public opinion polls and other studies?

Before diving into the details, keep in mind that some surveys ask about Hispanic origin and race separately, following current Census Bureau practices – though these are soon to change.

One way to count Hispanics is to include those who say they are Hispanic, with no exceptions – that is, you are Hispanic if you say you are. Pew Research Center uses this approach in our surveys, as do other polling firms such as Gallup and voter exit polls .

The Census Bureau largely counts Hispanics this way, too, but with some exceptions. If respondents select only the “Other Hispanic” category and write in only non-Hispanic responses such as “Irish,” the Census Bureau recodes the response as non-Hispanic.

However, beginning in 2020 , the bureau widened the lens to include a relatively small number of people who did not check a Hispanic box on the census form but answered the race question in a way that implied a Hispanic background. As a result, someone who answered the race question by saying that they are “Mexican” or “Argentinean” was counted as Hispanic, even if they did not check the Hispanic box.

From the available data, the exact number of respondents affected by this change is difficult to determine. But it appears to be about 1% of Hispanics or fewer, according to a Pew Research Center analysis of U.S. Census Bureau data.

How do Hispanics identify their race in Census Bureau surveys?

In the eyes of the Census Bureau, Hispanics can be of any race, because “Hispanic” is an ethnicity and not a race. However, this distinction is subject to debate . A 2015 Center survey found that 17% of Hispanic adults said being Hispanic is mainly a matter of race, while 29% said it is mainly a matter of ancestry. Another 42% said it is mainly a matter of culture.

Nonetheless, the Census Bureau’s 2022 American Community Survey (ACS) provides the self-reported racial identity of Hispanics: 22.5 million single-race Hispanics identified only as “some other race.” This group mostly includes those who wrote in a Hispanic origin or nationality as their race. Another 10.7 million identified as White. Fewer Hispanics identified as American Indian (1.5 million), Black (1.0 million) or Asian (300,000).

Multiracial Hispanics

Another roughly 27.5 million Hispanics identified as more than one race in 2022, up from just 3 million in 2010.

Growth in the number of multiracial Hispanics comes primarily from those who identify as White and “some other race.” That population grew from 1.6 million to 24.9 million between 2010 and 2022. The number of Hispanics who identify as White and no other race declined from 26.7 million to 10.7 million.

The sharp increase in multiracial Hispanics could be due to several factors, including changes to the census form introduced in 2020 that added more space for written responses to the race question and growing racial diversity among Hispanics. This explanation is supported by the fact that almost 25 million of the Hispanics who identified as two or more races in 2022 were coded as “some other race” (and wrote in a response) and one of the specific races (such as Black or White). About 2.6 million Hispanics identified with two or more of the five major races offered in the census.

Changes for the 2030 census

The 2030 census will combine the race and ethnicity questions , a change that other federal surveys will implement in coming years. The new question will add checkboxes for “Hispanic or Latino” and “Middle Eastern or North African” among other race groups long captured in Census Bureau surveys.

Officials hope the changes will reduce the number of Americans who choose the “Some other race” category, especially among Hispanics . However, it’s worth noting that public feedback has raised a variety of concerns, including that combining the race and ethnicity questions could lead to an undercount of the nation’s Afro-Latino population .

Is there an official definition of Hispanic or Latino?

In 1976, Congress passed a law that required the government to collect and analyze data for a specific ethnic group: “Americans of Spanish origin or descent.” That legislation defined this group as “Americans [who] identify themselves as being of Spanish-speaking background and trace their origin or descent from Mexico, Puerto Rico, Cuba, Central and South America, and other Spanish-speaking countries.” This includes around 20 Spanish-speaking nations from Latin America and Spain itself, but not Portugal or Portuguese-speaking Brazil.

To implement this law, the U.S. Office of Management and Budget (OMB) developed Statistical Policy Directive No. 15 (SPD 15) in 1977, then revised it in 1997 and again in March 2024. In the most recent revision, OMB updated racial and ethnic definitions when it announced the combined race and ethnicity question. The current definition of “ Hispanic or Latino ” is “individuals of Mexican, Puerto Rican, Salvadoran, Cuban, Dominican, Guatemalan, and other Central or South American or Spanish culture or origin.”

The Census Bureau first asked everybody in the U.S. about Hispanic ethnicity in 1980. But it made some efforts before then to count people who today would be considered Hispanic. The Census Bureau also has a long history of changing labels and shifting categories . In the 1930 census, for example, the race question had a category for “Mexican.”

The first major attempt to estimate the size of the nation’s Hispanic population came in 1970 and prompted widespread concerns among Hispanic organizations about an undercount. A portion of the U.S. population (5%) was asked if their origin or descent was from the following categories: “Mexican, Puerto Rican, Cuban, Central or South American, Other Spanish” or “No, none of these.”

This approach indeed undercounted about 1 million Hispanics. Many second-generation Hispanics did not select one of the Hispanic groups because the question did not include terms like “Mexican American.” The question wording also resulted in hundreds of thousands of people living in the Central or Southern regions of the U.S. being mistakenly included in the “Central or South American” category.

By 1980, the current approach – in which someone is asked if they are Hispanic – had taken hold, with some changes to the question and response categories since then. In 2000, for example, the term “Latino” was added to make the question read, “Is this person Spanish/Hispanic/Latino?”

What’s the difference between Hispanic and Latino?

“Hispanic” and “Latino” are pan-ethnic terms meant to describe – and summarize – the population of people of that ethnic background living in the U.S. In practice, the Census Bureau often uses the term “Hispanic” or “Hispanic or Latino.”

Some people have drawn sharp distinctions between these two terms . For example, some say that Hispanics are from Spain or from Spanish-speaking countries in Latin America, which matches the federal definition, and Latinos are people from Latin America, regardless of language. In this definition, Latinos would include people from Brazil (where Portuguese is the official language) but not Spain or Portugal.

Pan-ethnic labels like Hispanic and Latino, though widely used, are not universally embraced by the population being labeled. Our 2023 National Survey of Latinos shows a preference for other terms to describe identity: 52% of respondents most often described themselves by their family’s country of origin, while 30% used the terms Hispanic, Latino, Latinx or Latine, and 17% most often described themselves as American.

The 2023 survey also finds varying preferences for pan-ethnic labels: 52% of Hispanics prefer to describe themselves as Hispanic, 29% prefer Latino, 2% prefer Latinx, 1% prefer Latine and 15% have no preference.

What is ‘Latinx’ and who uses it?

Latinx is a pan-ethnic identity term that has emerged in recent years as an alternative to Hispanic and Latino. Some news and entertainment outlets, corporations , local governments and universities use it to describe the nation’s Hispanic population.

However, its popularity has brought increased scrutiny in the U.S. and abroad . Some critics say it ignores the gendered forms of Spanish language, while others see Latinx as a gender- and LGBTQ+-inclusive term . Adding to the debate, some state lawmakers favor banning the use of the term entirely in government documents; Arkansas has done so already .

A 2023 survey found that awareness of Latinx has doubled among U.S. Hispanics since 2019, with growth across all major demographic subgroups. Still, the share of Hispanic adults who use Latinx to describe themselves is statistically unchanged: In 2023, 4% said they use it, compared with 3% in 2019.

Latinx is also broadly unpopular among Latinos who know the term. Three-in-four Latino adults who are aware of Latinx say the term should not be used to describe Hispanics or Latinos.

The emergence of Latinx coincides with a global movement to introduce gender-neutral nouns and pronouns into many languages that have traditionally used male or female constructions. In the U.S., Latinx first appeared more than a decade ago, and it was added to a widely used English dictionary in 2018.

What is ‘Latine’ and who uses it?

Latine is another pan-ethnic term that has emerged in recent years. Our 2023 survey found that 18% of U.S. Hispanics have heard of the term.

Similar to familiarity with Latinx, awareness of Latine varies by age, education and sexual orientation. Among Latinos, awareness of Latine is highest among those ages 18 to 29 (22%), college graduates (24%) and lesbian, gay and bisexual adults (32%).

How do factors like language, parental background and last name affect whether someone is considered Hispanic?

Many U.S. Hispanics have an inclusive view of what it means to be Hispanic:

• 78% of Hispanic adults said in a 2022 Center survey that speaking Spanish is not required to be considered Hispanic. English-dominant Hispanics were more likely than Spanish-dominant Hispanics to say so (93% vs. 64%).
• 33% of Hispanic adults said in a 2019 survey that having two Hispanic parents is not an essential part of what being Hispanic means to them. Another 34% said it was important but not essential and 32% said it was essential.
• 84% of Hispanic adults said in a 2015 survey that having a Spanish last name is not required.

Views of Hispanic identity may change in the coming decades as broad societal changes, such as rising intermarriage rates, produce an increasingly diverse and multiracial U.S. population .

Today, many Hispanic families include people who are not Hispanic:

Spouses: Among all married Hispanics in 2022, 22% had a spouse who is not Hispanic. And in a 2023 Center survey , 27% of Hispanics with a spouse or partner said their spouse or partner is not Hispanic.

Newlyweds: In 2022, 30% of Hispanic newlyweds married someone who is not Hispanic. Among them, 41% of those born in the U.S. married someone who is not Hispanic, compared with 11% of immigrant newlyweds, according to an analysis of ACS data.

Parents: Our 2015 survey found that 15% of U.S. Hispanic adults had at least one parent who is not Hispanic. This share rose to 29% among the U.S. born and 48% among the third or higher generation – those born in the U.S. to parents who were also U.S. born.

What role does skin color play in whether someone is Hispanic?

In surveys like those from the Census Bureau, skin color does not play a role in determining who is Hispanic or not. However, as with race, Latinos can have many different skin tones. A 2021 Center survey of Latino adults showed respondents a palette of 10 skin colors and asked them to choose which one most closely resembled their own.

Latinos reported having a variety of skin tones, reflecting the diversity within the group. Eight-in-ten Latinos selected one of the four lightest skin colors. By contrast, only 3% selected one of the four darkest skin colors.

A majority of Latino adults (57%) say skin color shapes their daily life experiences at least somewhat. Similar shares say having a lighter skin color helps Latinos get ahead in the U.S. (59%) and that having a darker skin color hurts Latinos’ ability to get ahead (62%).

Are Afro-Latinos Hispanic?

Afro-Latino identity is distinct from and can exist alongside a person’s Hispanic identity. Afro-Latinos’ life experiences are shaped by race, skin tone and other factors in ways that differ from other Hispanics. While most Afro-Latinos identify as Hispanic or Latino, not all do, according to our estimates based on a survey of U.S. adults conducted in 2019 and 2020.

In 2020, about 6 million Afro-Latino adults lived in the U.S., making up about 2% of the U.S. adult population and 12% of the adult Latino population. About one-in-seven Afro-Latinos – an estimated 800,000 adults – do not identify as Hispanic.

Are Brazilians, Portuguese, Belizeans and Filipinos considered Hispanic?

Officially, Brazilians are not considered Hispanic or Latino because the federal government’s definition applies only to those of “Spanish culture or origin.” In most cases, people who report their Hispanic or Latino ethnicity as Brazilian in Census Bureau surveys are later recategorized – or “back coded” – as not Hispanic or Latino . The same is true for people with origins in Belize, the Philippines and Portugal.

An error in how the Census Bureau processed data from a 2020 national survey omitted some of this coding and provided a rare window into how Brazilians (and other groups) living in the U.S. view their identity.

In 2020, at least 416,000 Brazilians — more than two-thirds of Brazilians in the U.S. — described themselves as Hispanic or Latino on the ACS and were mistakenly counted that way. Only 14,000 Brazilians were counted as Hispanic in 2019, and 16,000 were in 2021.

The large number of Brazilians who self-identified as Hispanic or Latino highlights how their view of their own identity does not necessarily align with official government definitions. It also underscores that being Hispanic or Latino means different things to different people .

How many people with Hispanic ancestry do not identify as Hispanic?

Of the 42.7 million adults with Hispanic ancestry living in the U.S. in 2015, an estimated 5 million people, or 11%, said they do not identify as Hispanic or Latino , according to a 2015-16 Center survey. These people aren’t counted as Hispanic in our surveys.

Notably, Hispanic self-identification varies across immigrant generations. Among immigrants from Latin America, nearly all identify as Hispanic. But by the fourth generation, only half of people with Hispanic heritage in the U.S. identify as Hispanic.

Note: This is an update of a post originally published on May 28, 2009.

• Hispanic/Latino Identity
• Racial & Ethnic Identity

Mark Hugo Lopez is director of race and ethnicity research at Pew Research Center .

Jens Manuel Krogstad is a senior writer and editor at Pew Research Center .

Jeffrey S. Passel is a senior demographer at Pew Research Center .

Latinx Awareness Has Doubled Among U.S. Hispanics Since 2019, but Only 4% Use It

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Title: a survey of multimodal composite editing and retrieval.

Abstract: In the real world, where information is abundant and diverse across different modalities, understanding and utilizing various data types to improve retrieval systems is a key focus of research. Multimodal composite retrieval integrates diverse modalities such as text, image and audio, etc. to provide more accurate, personalized, and contextually relevant results. To facilitate a deeper understanding of this promising direction, this survey explores multimodal composite editing and retrieval in depth, covering image-text composite editing, image-text composite retrieval, and other multimodal composite retrieval. In this survey, we systematically organize the application scenarios, methods, benchmarks, experiments, and future directions. Multimodal learning is a hot topic in large model era, and have also witnessed some surveys in multimodal learning and vision-language models with transformers published in the PAMI journal. To the best of our knowledge, this survey is the first comprehensive review of the literature on multimodal composite retrieval, which is a timely complement of multimodal fusion to existing reviews. To help readers' quickly track this field, we build the project page for this survey, which can be found at this https URL .

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